Voxel51 employees share about the company’s culture, values, and mission, as well as the opportunities for growth and development within the organization. From an open source project to an enterprise product, Voxel51’s visual AI is used worldwide in academic research labs, startups, and Fortune 10 companies. A fully-remote Series B startup, they are building a platform that empowers machine learning teams to create more accurate, less biased AI across a number of exciting fields (healthcare, security, self-driving cars).

VOXEL51 IS HIRING!

• Principal Software Engineer (Remote)
• Machine Learning Customer Success Engineer (Remote)
• Sales Development Representative (SDR) (Remote)

From an open source project to an enterprise product, Voxel51’s visual AI is used worldwide in academic research labs, startups, and Fortune 10 companies. The engineering team is growing, and looking to hire skilled engineering managers to help us continue to build out the organization and culture. Please consider applying! If you have any questions, please feel free to shoot Josh an email (josh@voxel51.com) or connect with him on LinkedIn. You can also meet Voxel51’s hiring managers at ELEVATE!

TRANSCRIPT

Remy Schor: I’ll start by just offering some basics about who we are. Series B, we raised our series B last April. Foundationally, we build a tool for tool who people who make AI, so visual AI engineers. What I really like to talk about, and I’m gonna ask to Josh to speak a little bit about our business and talk a little bit about the culture.

Remy Schor: What I really like to talk about is from a sort of collective community standpoint – we are completely distributed. We have folks all over the US and Canada, currently just in North America. We’re all within a couple of time zones of each other, so we were able to sync quite regularly throughout the week, and then we communicate asynchronously with Slack.

In terms of the team and how we’ve grown, we are now almost 50 people, which is a really exciting and a turning point for us. Josh is gonna talk a little bit more about just statistically how we’ve gotten there, but I can say sort of spoiler alert that we doubled our headcount over the last 12 months exactly. Both Josh and I are new since then, new in that interim period, but, you know, have been heads down growing engineering and, and some go-to-market strategy hiring as well.

I’ll just circle back to the piece that I started to started to talk about with respect toour distributed environment. We really believe that people do their best work when they’re in a comfortable space, and for most people, that’s some version of home, home office, coffee, local coffee shop, local WeWork, what what have you.

What what we really do by allowing people to work where they’re most comfortable is we meet them right where with, with we meet them where they are with whatever they’re working on professionally and then also personally Whether it’s having pets, I’m not sure if you all could just hear my dog barking, I’m hoping no one could hear her. Awesome. Basically accommodate, right?

We are inclusive through accommodation, whether that’s people dealing with pets, they’re pet parents or they’re people parents or they’re, you know, taking care of of other folks and their families and their lives, managing extracurriculars, right? Continuing to learn, having that growth mindset. And so I think we really have created an environment where all of that is quite encouraged and supported. Josh?

Josh Leven: Yeah. Awesome. Thank you Remy. Hi everyone, I’m Josh, VP of engineering at Voxel51. Lemme just start by giving you just some basics about our engineering team. As Remy said, we’re fully remote all in North American time zones. We have 20 engineers today that are divided up into four squads of three to six people, three to seven.. actually we just hired one.

Our tech stacks are Python on the backend and TypeScript everywhere, but that’s I guess how TypeScript works. We are not so much a SaaS product, we’re primarily deployed into our customer’s cloud or on-prem. Our customers care very deeply about the security of their data and so they prefer to keep that in their own in environment, and so we again meet them where they are to help them be successful. As Remy said, I’m also relatively new, joined about six months ago. Lanny here is the elder statesman in this conversation,

I just wanted to share a little bit about the biggest reasons for me to join and one of those is really the impact that the product has. As you’ve probably noticed, the AI revolution is coming or maybe even already here. What we get to do is enable those teams that are building AI models to build models that are less biased, more safe, more reliable, more accurate. It helps them get this new magic out into the world in a way that helps everybody. And, and we’re helping in a ton of different industries, healthcare, autonomous vehicles, robotics, agriculture, retail, sports, and more that I’m not even listing.

We’re also not just for big companies. We have a vibrant open source community, include students and researchers and academia to machine learning professionals. And, and of course we do have a growing community of enterprise customers. Another thing I really love about working here is we’re we’re not just building a great product, but we’re also making big investments into innovation. Remy mentioned that series B we raised last year and we used some of that money to hire up a team of machine learning, pure research folk led by one of our co-founders, Jason, who’s a research professor at University of Michigan.

And what’s great is that they do this groundbreaking research that we then get to incorporate into the product, and being able to talk about the stuff that they’re doing is, is one of the ways we continue to be a part of like the conversation in cutting edge artificial intelligence. It’s not just for like marketing purposes, not just for the product.

We, we also wanna include everyone at the company. Every week we have a meeting called ML paper review, or every other week, where someone will take one of these papers that’s in the cutting edge of research and present it to the company so we can all grow and learn. All right. With that, let me hand things over to Lanny, one of the engineers on our team working most directly with the machine learning team and she can talk more about what it’s like to work here.

Lanny Wang: Yeah. Hi, my name is Lanny. I’ve been working at Voxel51 for two years and a half. I worked on the open source app and in the enterprise as well. Working in Voxel51, I feel one thing I really enjoy is actually working with people who are actually kind and very respectful. It is just a pleasure to like work with them and we work in a very remote setting, but you never feel like you’re working actually in silo.

We communicate a lot and for me, I feel I actually know all the engineers, not only the one within my squad on every topic. Whenever I think it, people who are relevant always, they’re super happy to when I reach out to them and have a good discussion. Also, the second point is I think we enjoy certain level of autonomy of being able to come up with the solution and the design of fixing something ourself and we have that trust among the team and having that flexibility.

Third, being in the rapidly growing space for AI and I feel in every squad, we’re able to tackle the most up to date problems in the industry. And that for me, like I feel very driven and excited for tackling those problems there. That’s the MLE, like they need the tools they’re facing every day. That get me very passionate and enthusiastic about the problem I’m solving.

Also the company, I feel we value the transparency and clarity a lot.

It’s not only we try to bring that from data insights, but also I feel within the org and engineers ourselves too, we try to have all the docs and meetings so it’s easy to find records even if it happened async, like we’re in there at the moment. Also as engineer, every year I think we can pick a conference to go, and previously I have been going to the CVPR, and today one of my coworkers shared a great news with me. He had a paper got accepted by ICML 2025 related to climate AI. He’s actually a software engineer, he’s not an MLE, so that’s really exciting. And that’s my perspective for working as an engineer in Voxel51.

Angie Chang: Great. This is the time that we normally go into breakout rooms, but I think today, since we have only two companies joining us and one of them is sick/out today, we’ll just stay here and I’ll ask you all more questions that I have prepared. But first I wanted to see if anyone else has a question in the chat or if you wanna raise your hand.

Remy Schor: Can I preemptively say that I’m gonna put my email address in the chat? People are starting to message me with my name. It’s gonna be hard for me to keep up so let me go ahead and put my email address in there right now, and if you do have a question or a curiosity after this meeting, you’re welcome to just shoot me an email directly. That would be really helpful. If you’re gonna do that, include your LinkedIn profile. Thank you.

Angie Chang: Great. So I’m looking through the chat and there is a questio. Are there opportunities for technical writing roles, documentation, or similar. Asked by Nessa.

Remy Schor: Nessa’s note is what prompted me to say let me share my email right now. Let me outline the roles we have open at the moment. Keeping in mind we are a small organization, we are hiring in a very disciplined capacity and we are hiring in a very disciplined capability. We are hiring and we are continuing to hire.

We have a Principal Engineering role open. This is full stack – I need somebody who has React and Python, that that’s the game plan, it’s principal level so they have to have some combination of hands-on coding, a desire to continue to write production code, architecture, design and mentoring. We’re not too married to number of years of experience, but this is a very senior position, so it’s not gonna be appropriate for somebody who’s early in their career.

I am hiring for a pretty nuanced Machine Learning Engineer This is specifically a machine learning engineer who wants to spend their time largely interacting with our enterprise clients. Not in a solutions capacity, right? I’ll clarify, we don’t have a services division, we’re not solving problems for our end user, but we are creating solutions with them. And so that’s really what this person will be doing 80% of the time. This machine learning engineer, ideally computer vision engineer, is relationship managing and, and solving problems with our users.

And then we have an SDR role open, which if y’all know an SDR that’s a sales dev sales development representative, it’s typically gonna be like a pretty non-senior salesperson. Somebody who does a lot of the basic kind of cold emailing, warm emailing, introducing.. If you’ve ever been pitched a something, a software solution, it’s probably those pitches are coming from SDRs. It’s a heavy lifting role, but it’s a really good way to break into software sales. And so typically we’d be looking for somebody with about a year’s worth of experience as an SDR – a little bit more flexibility with that one, if anybody has any questions about those roles specifically, that’s what I’m gonna about to put my email address in the chat to answer, and you’re welcome to reach out directly.

Angie Chang: The next question that I see here is, how does product management fit into AI industries?

Josh Leven: That sounds like a Josh question. Yeah, so I I don’t see who asked that, but just to clarify, you’re asking like, how do we use…

Angie Chang: Susan G?

Josh Leven: Susan awesome. Susan, are you asking how do we use product management to deliver what we’re building? Or are you asking how we see our customers using it? Awesome. Yeah, so we, we use it I don’t think in a particularly innovative way. Our product manager still does the sort of things you would expect, gathering ideas and insights from our customers, from people internal to the company, from wherever else ideas can come from, works those ideas into something more concrete and solutions to actual problems and puts ’em through like a product development process.

They’ll go through design, they’ll get verified, like we’ll put it those designs in front of our customers and get their feedback. They’ll work with the engineers to break it down into tickets. And then of course there’s on the more research side, during that kind of ideation phase, there’s a conversation that happens about where do we see potential research complementing a feature like this?

What’s something we can do to build this feature? Not really like just the way a competitor might build it, but in an innovative way or give it capabilities that nobody else in the industry has. Or sometimes it’s even like, what are we seeing our customers trying to do that we think we might be able to research a solution for them so that they can achieve their goals through us more easily than having to build it themselves. How did I do Susan? Does that basically answer your question? Awesome, thanks so much for asking.

Angie Chang: The next question I see is about the interviewing process from Laura. Curious about your thoughts on multiple round interviews.

Some companies have up to six rounds.

– Yeah, I can take that one.

I’m actually just scrollingup to see if I can identify.

Okay, Laura. Got it.

Yeah, so it does dependon the open role, right?

How many rounds we do.

I will say that I, Ithink we work very hard

to be quite thoughtfulabout utilizing the,

the candidate’s time appropriately

and making sure that we’regetting enough information so

that we can make an informed decision.

Josh in particular isprobably the most thoughtful

interviewer I’ve ever hadthe pleasure of working with.

Don’t tell my otherexecutives that I said that.

It’s really extraordinary. Imean truly I’ve been recruiting

for 20 years and I feel I’velearned more from Josh in the

last six months

as a point person hiringmanager than probably

anybody in my whole career.

So that’s been really great.

Maybe I should let himanswer this question here.

Here’s what I’ll say for,for a leadership role.

Yeah, there, there’sprobably gonna be six rounds.

We’re we, we don’t, youknow, often assign any type

of take home technical tests.

That’s not really our, our approach.

We want, you know, sort of realtime conversational kind of,

you know, resembles aday-to-day situation,

type in interview process.

But you know, you gotta meetboth co-founders, right?

And you have to meet Josh probably twice.

He is the VP and if you’re interviewing

for a very senior role, I, I,

I mean I would wanna meethim more than once, right?

He’s gonna be your direct manager.

That’s four conversations right there.

Plus you still wanna meet at least one

or two engineers from theteam in some capacity.

So there’s your six. If I’m a senior,

if I’m a software engineering manager

or you know,

to some extent possibly eventhis principal engineer, I mean

that, to me that feels prettyreasonable even though it

sounds like a big number.

What I will say is we,

I manage all of recruiting,including scheduling,

and I’m relentless with scheduling.

Josh can attest.

So if, if there’s a positive signal

and both parties are quite interested,

even though there mightbe a number of steps,

they can happen rather quickly

and we do our very best

to schedule them inlike a very appropriate

manageable amount of time.

Typically I shy away fromsetting up individual interviews

that are more than 90 minutes.

I think that starts toget a little too lengthy,

but it’s possible

to meet two separatepeople on the same day.

I will say for anybodyin this market right now,

and anybody who’s sort ofearlier in their career,

y’all don’t, y’all maybe don’tknow what it used to be like.

You used to have to go on site

to the company’s actual office,

even if you didn’t live in their city

and sit for eight, you know, hours

of interviews for a whole day.

That’s what it, that’s what it was like.

It’s obviously not like that anymore.

We do everything virtually

and so we make it accessibleeven though it may feel like

quite a few steps for anon-leadership non very senior

role, try to keep itto three or four steps.

There’s just fewer peopleto meet at that level.

Hopefully that answersyour question, Laura.

If any clarificationsare needed, by all means

– For the record, I havenothing to add to that Remy,

– Except you remember Joshprobably back in the day having

to put on a suit, go to anoffice, you know, sit in front

of a bunch of people youdidn’t know for hours

and hours, maybe eat lunch with them.

I don’t know, it was likea totally different scene.

– Yeah,- Interviewing virtually is

quite a delight. Frank, I

– Remember my first jobs werein New York where I did have

to put on a suit and thenI moved out to California

and I went to my first interview in a suit

and everyone was veryconfused and never did it

– Again.

Yeah, that, that’s true.

There are definite coastal differences

and also just, I mean it’sjust, everything’s changed.

Now

– We have a question fromJulissa Cillo that says,

can you talk about the ML AI stack?

Are you hosting your own train models

or leveraging third party providers?

And if so, which ones?

– Yeah, yeah, great question.

I I may not know this as well as Lanny.

So Lanny, please correctme if I get this wrong

or do you know the answer?

And you can just answer it.

– We are data centric,so we actually are open

and very flexible.

So in people’s AI stack,like we are not the throttle

that you would have, we we integrate

with all the popular tools actually.

– Yeah, exactly.

So we, we, you can easily like load

and apply tree trained pre-trained models.

We have this thing calledthe model zoo that’s full

of models that you can just kind of grab

and run using the system.

And then we have, yeah,as Lanny said, all sorts

of integrations, but we’renot directly as like part

of our system likehosting models on any kind

of external provider.

– There’s a questionfrom Garima about a tech

program manager role.

Is there any maybe opening in the future?

– No, I mean that’s thekind of thing that it’s,

it’s pretty tough to predictexactly what we’ll be hiring

for in 2026.

That’s not on the mapfor 2025. But email me

– A question from Ashley Spear.

What are you looking foras a cultural fit for Yeah.

Culture fit?

– What landing Lanny jump in?

Do you wanna get in the loophere and chat about that?

– Yeah, I think first of all,like being a genuine person

to communicate with because noone like to work with like Al

and then second being alsoable to work very independently

because we are trying to solve the issues

that we’re working with liketo a certain degree level

because we are remote.

And so being able to, toget deep into the things

and push it forward yourself, that’s,

and also when there is an issue, I love

that in general here,

rather than complaining aboutit, usually people look at,

okay, what things need to be done

and then we start working on it.

– Yeah, thanks Lanny. I’lladd one or two things to that.

I, I think it’s, it’sreally important that we’re,

we’re building a a cultureev every new person you

hire adds to the culture, right?

And it’s important we’rebuilding a culture that is,

is low ego.

We’re not looking for people

who think they have all the answers,

but ones who are good atcollaborating with their squad

and helping to pull outeveryone’s great ideas

and have the best ones rise to the top.

And yeah, a able to have likereally good collaboration

and productive conversations,willing, willing

to jump in and, and help one another.

’cause as much as people do like

to get heads down whenthey run into an issue,

they’re quick to post iton Slack as they should be.

And there is always an outpouring

of people be like, oh,have you tried this?

Have you tried that? Lemme jump in.

And it’s really important.

What we’re building is complicated

and building it to work

with every possiblecustomer scenario makes it

even more complicated.

And so there’s a lotof wisdom on the team,

people who’ve been there a lotlonger than me who are able

to help everybody navigate that.

– And I’ll just add a sortof personal theory I guess,

or philosophy I have is

that if somebody hasdemonstrated the capacity

to care deeply about somethingin their life, right?

And whether it’s anextracurricular, could be a sport,

could be they don’teven have to be playing.

Like they absolutely love the Lakers.

Like if they, if somebody demonstrates

to me in the first conversationthat they have passion

for something, I believe then

that they can have passion for their job.

And so that’s like a reallygood signal for me typically.

So when you, you’re probably,

you may hear differentperspectives on this,

but if there is anopportunity in your interviews

to just tie something back to

what you do on the weekends, right?

The manager mentions a bookthat you happen to have read

or something like that, right?

You know, even if, even ifyou’re just asking the person,

Hey, what do you do on the weekends?

What are you, what are you looking

forward to doing this weekend?

And you can tie that back towhat you do personally for me,

that’s a really good signal.

So I do look for that.

It’s, it’s part of whatdifferentiates people, right?

And people hire people, so be a person.

– Okay. I am gonna ask aquestion from Sha GTA about the

hiring process.

Us, does W Cell 51 focusprimarily on visual AI

and computer vision models from

what you saw on the,they saw on the website?

Or do you also work with datamodels in other AI domains?

– Yeah, great question. Soright now we are 100% focused on

computer vision use cases.

Is that always gonna be the case?

Can’t say, but, but rightnow that is really our focus.

And I, I can say this confidently,

that’s gonna be our focus this year,

but we’re always havingconversations about other places we

can expand into.

It’s a really exciting space

and the the kind of things that we do,

which is basically helppeople to leverage their data

to build great models isnot specific to visual ai.

So there’s a lot of opportunity there.

– Great. So question fromLaura Monson about the

interview process.

Wait, did we already do that?

Sorry, it just keepsjiggling this little chat

window a question.

Can you from Abigail,

could you talk a bit moreabout the AI privacy,

security issues you’re tackling?

– Hmm.

So the,

– So Abigail, when you saythe ones that we’re tackling,

do you mean I feel like I’m

asking the same question I asked before.

Are you saying like the privacy

and security issues that wetackle for our own software

or how we help our customerswith the privacy and privacy

and security of the AI they’re building?

Sure.

So because we

deploy everything intoour customer’s clouds

and into their prem,

our issues about AI privacyand security aren’t so big.

And the, I mean certainlywhen we make our own models,

we’re very thoughtful about

what data we’re using to train it.

I mean, using data to trainmodels is kind of the thing

that we do and help to do.

And we’re certainly likenot taking proprietary data

or we’re, we’re not like we’rebeing very responsible about

the data that we use to, totrain the models that we do.

But the, the application that we make

full of the, the pre-trained models

and the models that our customersare making using the data,

it’s because it’s all on-prem.

We don’t have to worryso much about their data,

data leaking through ourproduct to go anywhere.

In fact, we have a, a number of customers

that have like a fullyair gapped solution that

of ours that they use.

So I guess one of the things

that we do is we buildan air gap solution.

So to just kind

of eliminate any concerns thecustomers could have about

how we’re handling privacy and security,

which I should add the teambuilt before I joined and,

and was a huge effort.

So landing and the rest of the team

should be very proud of that.

It’s not most companiesthat are scale that,

that have an air gap solution

and it’s, it’s been agreat advantage for us

in the industry to be able to offer that.

– Sodi d has asked aboutthe technical interview.

What are your thoughts on usinghacker rank style interviews

given AI tools like copilot issomething developers use on a

regular basis for adeveloper productivity?

– Oh, can I,- Yeah.

– Oh you go, you got

– It.

Well, I was just gonna say,I just, I just don’t care

for hacker rank style interviews.

I think they’re, they don’t

appropriately mirror whata day, the day-to-day life

of an engineer looks like.

Furthermore, it’s, it’s essentially,

it’s a test you can prepare effectively

for hacker rank style questions

or lead code style questions,

but I don’t really think it’sdoing anybody any favors.

I will say, and maybe, I meanI want Josh to answer this

’cause he’s excited andthat makes me happy.

But I,

if you’re ever using AI in an interview,

the interviewer knows,

it doesn’t matter if youthink they don’t know,

they know now they may havesaid you can, which is fine

by all means, but you’renever like getting away

with it just FYII don’tthink that so deepti

that you’re trying to, I’mjust saying like for everybody

overwhelmingly, if you are as a recruiter,

what I see a lot is I’ll jumpinto a first conversation

and the person won’t havedone research, which is

a different conversationfor a different time

and I can see that they’relooking us up real time

and reading to me what we do.

And I have to time out.

I don’t need you to pitch me right, tell,

you know, I have to like backtrack.

So I, we can always tell whenyou’re using your computer

to look up something up,whether it’s AI or not, Josh.

– Yeah. So to totally agree with that.

I’m, I’m very much against those sort

of hacker rank lead code style interviews

with or without ai.

When, when I think of technicalinterviews, my goal is

to put you in an environmentthat is as similar as possible

to what you’ll be doing day to day, right?

So if you code with ai,then you should be coding

with ai, right?

If you’re normally able to usewhatever libraries you want

and Google answers to things

and talk something throughwith somebody else, then all of

that should be availableto you in the interview.

And so that’s kind of howwe like to structure the,

the coding part of thetechnical interview.

It’s like as close aspossible to like pairing

with a colleague in your ownenvironment on the language

that you’re most comfortablewith on a problem

that like is not a lead code problem,

that we can have aconversation about trade-offs

and software design

and like all the sort of things

that you normally have conversations

with your teammates about when you’re

actually completing a ticket.

And that’s, that’s what the

technical interview’s about for us.

– So I guess we can go on to our questions

that we came up with.

If someone else is gonna askquestions, I’ll ask questions.

What are some qualities

and experiences that makesomeone successful at Oxil 51?

– Yeah, I mean I think it’sa combination of some of

what we’ve already shared,certainly curiosity, right?

Definite passion for what we’re building.

I don’t know that youhave to come in with that.

I mean, it certainly helps,

but once you get the lay ofthe land, like really diving in

and, and wanting to be here

and wanting to be part of whatwe’re building, being kind

and thoughtful, I thinkto be sure, you know,

I, I am nine out of 10, 99 out

of a hundred times the very first person

that somebody interactswith with respect to voxel.

And so from a candidate standpoint,

and so there are some things

that are important to me, right?

Like, I don’t care if you’rerunning late, I do need you

to let me know, right?

As an example, right?

And again, it like, things happen,

issues pop up occasionallyI’m running late, right?

Like I get it, we all have,but that being like transparent

and communicating is really important.

I had another point I was gonna make,

well I mentioned curiosity

because I think that’s the big one,

really understanding the whybehind what we’re building

and then kind of bringing yourown, bringing your own why

to the table, Josh?

– Yeah, the that’s great.

The, the only thing Iwould add is we are still

very much a startup.

We’re not planning like multiple quarters

ahead in detail.

Although only we have likea, a broad road roadmap plan.

Like things come up in likea partnership or a customer

and we surprisingly need

to drop everything and jump on that.

So having a certain levelof flexibility if you’re,

if you’re used to moreof a big company job

where things are all laid out

and nothing ever interrupts your sprints,

like we do everything we can

to not interrupt the sprintlike we do try to respect that,

but much more than otherplaces things are gonna come up

and people who can get excitedthat, oh man, you know,

if we switch gears right here,

we have this huge opportunity,

you’re gonna be a lothappier than if you get

frustrated every time something comes up.

– So we have a question from Abby.

What types of companiesdo y’all hope to work with

and what tasks are the AI used for?

– I mean Oh yeah, leaning you go.

– We work with a wide range of industries

from autonomous driving to the fence

and from modern agriculture

to robotics.

Yeah. So it’s, it’s very satisfying.

Like sometimes seeing the

customer success engineerpost the, the abstraction

of the problem, likethe customer encounter

and see the scenario thatlike we were able to, to help.

Yeah. So we, it doesn’t,

we don’t really have a specific setting

or a specific industrythat we’re anchored to.

It’s really a wide range ofapplications that can on issues

that we can solve from, from visual ai.

So any AI industry that workwith visual images, videos,

3D point cloud, et cetera,we can work with that.

– I have a question is whatways does Box L 51 engage

with the open source community

to drive the data centric AI revolution?

– What a, well,- First, every way.

– Yeah. Sorry, Ram didyou wanna start answering

– In, in every way?

But I’ll Josh, you, you, you go ahead.

– Oh yeah, I mean, I’llname a couple of ways.

Like we, we have a vibrantdiscord that we maintain

to like support peoplein their 51 journey.

We have a whole bunch of events,

meetups, hackathons,

man, actually trying tothink of all the stuff,

like we have a wholecommunity slash dere team

that just spends a hundred percent

of their time supporting our community.

I couldn’t possibly someone else jump in

and remember all theother things that they do.

– Yeah. And also on GitHub,

we actually have a very active community.

We have this thing called51 plugins that allows

to transform.

So a lot of the MLEs, theyknow Python really well,

but they don’t write react or type script,

but they hope to use the applike to make a little tweak

and then they can use it better.

So that plugin system allowthem to, to use Python code

to generate that ui, to buildtheir unique workflow for them

and they will share itin the, in on GitHub.

So that allow us to see,hey, what people are,

are working on, what’s the need?

And we do work with theengineers there too, to just

bring the new features in

and merge new things from the community.

So it’s a very active community.

– Sha g is asking outta curiosity,

why is the product called 51?

– I please go ahead, Laney.

– I listened to one of thepodcasts done by Jason and Brian

and they did talk about the name VAO 51.

Where it come from Vao is thepixel in the video setting,

a three dimensional setting.

And then 51 came from theunknown, the alien zone 51.

So it’s meaning that we’reexploring some unknown.

– I think that’s the true answer.

I was given a different answeryears later when I joined.

Voxel still means vox a 3D Pixel,

but I said, you know, our,

our product helps you finda needle in a haystack.

So you know, if youhave a thousand needles,

which needle is it thatyou’re looking for?

Maybe it’s needle 51.

– Okay,- From Angela,

what is the workflow fromcustomer request to end solution?

Is the data a mix ofsynthetic and annotated?

And as a part of thatprocess, are you also working

with human annotators?

– Okay, I think, Ithink I can answer this.

– So we, if you’re talking about what,

what does the customer,what’s the customer workflow

as they’re using us tosolve their problem,

and how does annotation connect with that?

Am I getting that right Angela?So when you say customer

request, it makes me thinklike they’re asking us

to do something, but reallyit’s, I think it’s, yeah,

so I’m, I’m gonna answer that question.

So customers, they come to us typically

because they have a ton of data

and they want to use thatdata to make an AI model.

Sometimes they’ve been tryingto make an AI model with

that data and they justcan’t get it accurate enough.

It’s, it’s got blind spots, it has issues

and they need, our product’s help

to get it over the finish line.

And so they use ourproduct to explore the data

and understand stands, right?

So, you know, there’s trainingdata and test data and,

and so they’ll look through the data

to see like what’s missingin their training data

that is preventing the modelfrom learning the things it

needs to learn to have a full solution

that covers all cases,

is like less biased isaccurate in more situations.

And so our product helps tokind of highlight those gaps

for them so they can figureout what additional data,

for example, they needto get labeling for.

And then they can label it and then

add it to their training set.

And then they use that to train the model

and then they check theaccuracy of the model again.

And there’s this like virtuous loop.

As the model gets better andbetter, then we highlight more

and more subtle areas where it can improve

and they get more labelingand they improve and they,

and so that’s, that’s kindof the, the cycle there.

We’ve got some coolthings in the works for

how we can help supportthe annotation side of that

that we’ll be announcing later this year.

But for now, we really kind of stay out

of the annotation business.

We are partners with a wholebunch of annotation companies

and so when it comesto the annotation part,

they’ll just shit ship themetadata over to to them

and they’ll, they’ll get thelabels and they’ll import the

labels over to 51 and,and the cycle continues.

– The next question fromAbigail is super loosely around

what percentage of employeesatel 51 are women or non and

or non-binary?

– 25%.

– Great. So that’s the lastquestion I see in the chat.

I’ll ask a question that we had prepared.

Does your company supportlateral career moves such

as switching between engineering product

or management roles?

– Yeah, absolutely.

You know, it’s a verymuch case by case basis,

but we’ve, we’ve had peoplemove in many directions.

We’ve had conversations withpeople about movement as well.

It’s, I think it’s, it’smy job as a a leader

and the managers of myteam, it’s, it’s our job

to support you in the growth

of whatever direction youwant to take your career.

Hopefully that’s something

that we can do within the company,

but you know, if not, thenI think part of our job is

to help you make that leapfrom us to the right place

for you to continue that growth.

– And how does Voxel 51support in new employees

during the onboarding process?

– Well, I think bigger picture,

it’s, it’s maybe not yettotally a scalable process

because our COO who’s incrediblespends like the first half

of the first day with everysingle person who starts,

there’s only one of him

and he has 100,000 other responsibilities.

So I’m trying to talk tostart the conversation about

how we can make more, morescalable iterative onboarding.

But it’s gonna be, it is goingto be a combination currently

of our COO, getting theperson situated on day one

and then handing them offto their direct manager

and the manager will takeover setting up, you know,

ensuring that they have alltheir appropriate one-on-ones.

They meet everybody, they get ramped up,

they have the right curriculum.

Another thing that ourdeveloper relations team does

earlier, someone had asked how we interact

with our open source community.

And the answer is, you know, as Josh

and Lanny both, both said,there’s a lot of avenues, one

of which is we have adedicated computer vision dev

re team.

They create a lot ofcurriculum and content.

So even

before someone starts, if they want to,

they can like watch theCoursera course on on, you know,

on voxel 51, they can checkout our LinkedIn learning lab.

There’s, there’s resources out there

and I, I believe that thosealso help with the onboarding.

And then we do twice weekly all hands.

So no matter when you start during a week,

typically it’s a Monday,you’ll get introduced

to the entire communityreal time virtually.

And there’s like a wholeseries of like shoutouts

and introductions and stuff.

– I’m gonna read anotherquestion from the chat, Melissa,

ask how does Voxel advisecustomers on infrastructure infra

as well, EEG computing,power memory storage,

and how often do infra needschange as models, amount

of models or nature of model data grow?

– Yeah, this is a great question.So we do absolutely there.

That’s a, a big part ofthe onboarding process

for new customers is advising them on how

to scale their infrastructure

and helping them to get it right

and helping them to adjust it over time

as those needs change.

It’s absolutely something we do.

We have a infrastructure team

and that helps set those kind of standards

and advise and it’s, aswe continue to develop,

like this year we have a biginitiative for performance,

we revise those guidelinesto say, oh, you know,

if you wanna take advantageof these performance

improvements, you’re gonnaneed more cores on these

machines and yada yada.

So it’s a, it’s an ongoingdeveloping thing that is a

central part of how we setup customers for success.

– As a question from Abby,

looking at y’all’s open source library

and GitHub, can this tool be used

to process non-visual datalike observability metrics

or complex texts?

– So with, with the caveatthat Lanny mentioned

that we have a very powerful plugin system

that you can do quite a lot with.

The, the core product rightnow is just images, video

3D meshes point clouds

and other kind of visual media.

But your, your questionleads us to the same thinking

that we have, that the sameapproaches we’re taking could be

expanded to other formats.

– So thank you for that. Angela asks

and says thank you, it helpson the scope of the product.

She notice defense workas part of the modeling.

Are you also looking at redteam and pixelated attacks?

Are you also suggestingemergent models to clients?

– So the, as far as like emergent models,

if I’m understanding thatcorrectly, we, the models zoo

that I mentioned, we try tostay pretty up to date on that.

So whenever new likeindustry models get released,

we are quick to add them to the zoo

so everybody can get access to them

and run them really easily inside of 51,

we the, like the customersuccess team and,

and Ramey was talkingabout, we’re, we’re looking

to hire one more person for that team.

They certainly do advise all

of our customers on bestpractices and strategies

and approaches that they may want to take

to help make their workas successful as possible.

They are more expert in me on

what strategies they recommendwhen, so I can’t answer

that particular question.

– Athena asks, how doyou maintain transparency

and collaboration ormanaging a remote team?

– So I, I don’t wanna justassume I should talk, but

– Go for it.

Okay. Has there,

– Thanks.

So maintaining transparency is like a

constant vigilance.

I think that’s like part of theresponsibility of leadership

to like go out of theirway to be sharing context

and being transparent aboutdecisions and directions

and possible directions.

That’s just a kind of decision

that we make at the leadership team.

One of the reasons I wasexcited to join as a VP here is

because I knew that was a corevalue of the leadership team

and it’s a basically anon-negotiable for me.

I don’t know how to lead ateam without being transparent.

So I, I think you get just like a,

everything just getseasier if you’re willing

to put in the time to betransparent with folks.

So, and I, I guess the restof the leadership team agrees.

So we, we do that

collaboration remotely is tricky

and it’s something that weare always talking about

and iterating on,

particularly remote acrossdifferent time zones.

And I think part of itis just figuring out

what are the key touch points

where collaboration is most valuable.

So, you know, we do ourregular sprint ceremonies

and so like planning outthe work we’re gonna do

for the next couple weeks ina sprint is an important touch

point for collaboration as wellas figuring out like where,

where do we need morecollaboration in order

to figure these ticketsout or come up with a plan

or, you know, the, one of the squads,

the backend squad is doing a lot

of tricky performance work right now.

And so, you know, there’sa lot of, you know,

a couple people get together

and do a brainstormingsession, write up a doc,

and then that they’ll share the doc

and then everyone comestogether and discusses the doc

and gives feedback and,

but it’s, I think it’s reallyabout just like creating the

right habits and processes

and figuring out those touch points.

I’m always a big fan of pushingfor just code pairing and,

and just sitting next toeach other virtually and,

and pairing on a problem,whether it’s coding

or writing up a doc orwhiteboarding or whatever.

And then, you know, like Isaid, time zones become tricky

because all right,

well one person ends their dayat 2:00 PM the other person’s

day, and so someone’sworking solo for three hours

and then the other person you’re pairing

with wakes up three hours before you.

And so making sure you havea clean handoff and a plan.

And so it’s a lot of communication,a lot of thinking ahead,

a lot of just being thoughtful.

– Thank you for that. So I seea question here from Julissa.

Is the open source project thesame one offered to clients?

And how important is the opensource aspect to the product?

– I mean, I’m not an engineer,but I’d be happy to jump in

and answer this unlessLanny wants to take it.

Maybe, maybe I’ll give my answer and Josh

and Lanny can, can holdme accountable in case

I’m missing something.

This is what I typically tell candidates.

So we are open source,we remain very committed

to being an open source community.

Our open source tool issingle user and local install.

So it it, it’s quite limited in the sense

that you can only work witha visual data set as large as

what your laptop can handle.

So three-ish years ago welaunched our enterprise solution.

The enterprise solution ishow we’ve monetized the main

feature differential right nowis that it’s a teams version

of the open source tool.

So it’s a collaborative toolthat also allows you, I mean in

so doing it allows you towork with your team in your

cloud in the same largescale visual data sets,

which is kind of solving its own problem,

but that’s the uniquity,it’s more scalable,

it’s more performant, more secure, right?

There’s enhanced security

and you know, forthcomingadditional features.

But that open source productwhile sort of part of

who we are just at our core also drives

and energizes users intothe enterprise tool, right?

So individual engineersfind the open source tool,

they love it, they energize,

and a lot of cases have in factcome to us asking to uplevel

to the enterprise solution.

There’s still obviously a sales cycle,

but it’s nice when they’vealready heard about us,

they already know they likethe tool I miss anything.

– Yeah, and I think previously it’s,

we emphasized more on thecollaboration, user management

and security side,

but I think started from this year

we added more advancedfeatures that for instance,

with data quality panel

and model valuation panel,

these advanced features willtap better into the enterprise

solution for industriesbetter scoping their

specific problems.

Yeah. But we remain very committed

to the open source community.

– So the ENG team soundsvery collaborative.

We’d like to dig intothe culture a bit deeper.

Are there any intentional

or surprising steps V 51 hastaken to create an inclusive

and supportive environment for women

or parts of the culture thatyou’re just really proud of?

– I mean, I think,- You know, the,

the biggest thing is again, you know,

we have this really remarkableCOO, our executive team

of course is awesome.

Our COO Dave is

particularly involved in just sort

of the day-to-day operations of course.

And, and he’s reallycommitted to continuing

to leverage whatever tools we need

to up level communicationup level, for example,

our recruiting effortswith respect to women

and non-binary folks

and you know, people who have been sort

of historically repressed in some way.

So I feel like

we’re still figuring out,

and I think this is not,there’s no solution,

there’s no one right way to ensure

that in organizations bothinclusive and, and welcoming

and comfortable for people.

But I think a good start is that we are

committed to dedicating the resources

to improving, right?

And we, we, we tap third party resources.

We’ve, we’ve, we’vebrought in some programming

that has helped us kind of

shore up our internalcommunication a little bit and,

and kind of work in a morecollaborative capacity.

Yeah, that’s, that’s just the beginning.

I mean, again, with just50 people, you know, I,

I really do feel likewe’re just getting started.

– Yeah. I I just add one thing that I,

I think it really, like,initiatives are great

and important, but I thinkwhat it really comes down to is

how it’s incorporated in the everyday.

I think every time we’re likedesigning an interview process

or running a meeting

or w whatever else we’re,we’re doing day to day,

there’s a part of us that’s thinking like,

how do we make sure we’redoing this in a way where yes,

w women feel comfortable,

but also, you know, quieterpeople feel comfortable.

Or people whose English isn’ttheir first language feel

comfortable, right?

Like inclusivity, inclusivity isn’t, like,

initiatives are helpful,

but what it really comes down

to is are you like being thoughtful in the

day-to-day things that you’re doing

– This question about, howdoes VLO 50 one’s mission

to bring transparency and clarity

to the world’s data influence your daily

operations and decision making?

– Does – It honestly influenceour day-to-day operations

and decision making?

I, I I, I think it’s a fair question.

Like, is is that a day-to-day question?

When I, when I think about amission statement like that,

I think it’s right at the coreof the more strategic stuff

that we do when we’re talking about like

of the different thingsthat we can do in 2025

to take the company tothe next level, right?

Like there, we, we talked about all sorts

of different opportunities

of like d different things we could build

and different types ofcustomers we could go after.

And, you know, conconsidering those options,

bringing clarity to theworld’s data is, you know,

a helpful thing to helpus decide between the,

when we’re making big decisions.

– What tools and platformsdoes VLO 51 utilize

to facilitate communicationand project management?

– So we use J lot.

All the status are in sync through Jira

and there has been some Confluencearticles, there are lots

of video records in our Google Drive.

Also the Slack channel.

If there is certain domain Ihaven’t touched for a long time

and I need something,I usually usually just

start through the slack.

Usually other people havealready brought it up.

Yeah, I would like to think myself as part

of the more quiet side

and there hasn’t been any likeproblem, I feel communicating

or being able to communicatewhat I think of very honestly,

like, feel very safeenvironment to work in.

– So for the principal engineerrole that you have open,

how does this rolecontribute to the development

and scaling of your enterprise solutions,

especially processing largescale visual AI data sets?

– Wow, I that’s so specific.

I hope that was taken rightoutta the job description.

’cause you, you reallyunderstand the role.

So the, the role is targeted for

one of the two squads that ismost focusing on performance

and reliability this year.

One of the challenges thatthe company is tackling

in 2025 is that the size of data sets

that our customers are usingis really starting to explode.

Where we would talk aboutlike a hundred thousand

samples in the data sets or maybe 500,000.

Now we’re talking to companies

who have 50 million samples in the dataset

where they’ll have a data lakewith a billion samples in it.

And so the challenge that

that squad is tacklingthis year is how do we

bring all of the power of51 to data, which is now,

now several orders

of magnitude more than the code was

originally intended to handle.

And the,

the challenges there areeverything from infrastructure

to backend to front end.

Because even when youfigure everything out,

there’s still an enormous amount of data

that you wanna show on the front end.

And you can’t show it all at once.