Mavik Ventures

I focus on Senior ML/AI Talent for LLMs, Generative AI, Deep Learning, NLP, Vector Databases, and more for startups and high-growth companies.

Senior Recruiter

Coupang

Contract-to-hire through Search Wizards. I built the ML/AI team at Coupang from L5-9 for Search and Discovery. Machine Learning (LLMs, Tensorflow, Pytorch, Deep Learning, NLP, Core Search, and Serving/Infra). Achieved 20 hires from January to September 2022 by increasing referrals and candidate quality. Closed >90% of offers.

Senior Principal Recruiter

Calendly

Sourcing and recruiting lead for the engineering team. Full desk tech recruiting, working with Tech leadership, HR and doing all sourcing.

Senior Technical Recruiter 

Ava Labs 

Global engineering sourcing and recruiting lead for technology and leadership positions for this post stealth mode DeFi startup. Worked directly with the founders on global engineering searches for frontend, backend, and smart contract developers.

Global Crypto Engineering Recruiting Lead 

Moss Search 

Moss Search specializes in recruiting for HFT trading firms in North America, Asia, and Europe. 

We specialize in searching for senior-level niche roles: Quants, Quant Devs, Researchers, Traders, HFT engineers, FPGA/ASIC and more. We recruit for firms that are at the forefront of advanced electronic trading.

Founder

Rich Moss

Omid Rhezaii

Zachary Ye

Jianxu (Ethan) Pan

Everything we do at Cleanlab is guided by our north star – to improve the world’s ML data more easily and quicker than any other solution – enabling AI systems to train more reliably on real-world, messy, error-prone data. We develop next-generation data-centric AI, open-source algorithms and provide no-code SaaS enterprise solutions to help individuals and teams at companies (across all industries) diagnose/fix issues in their datasets and produce more reliable ML models by providing clean labels for training.While many companies can help store/manage data or develop ML models, there exist few solutions today to improve the quality of existing data, which is the core asset of the modern enterprise. This is where you come in. At Cleanlab, you’ll be able to take ownership of critical projects that pioneer the future of data-centric AI.We are a hybrid company, with over half of our team (and office) located in San Francisco.

Co-founder and Chief Scientist

Cleanlab

Cleanlab’s mission is to democratize safe, trustworthy, and reliable AI. We believe the most promising path to such AI follows a data-centric approach. We build open-source algorithms and no-code SaaS solutions based on our research to help individuals and teams systematically and algorithmically curate high-quality datasets, which enables AI systems to train reliably on real-world messy and error-prone data.As a backend software engineer at Cleanlab, you will be responsible for building the backend APIs that power <a target="_blank" rel="noopener" class="A_embeddedLink__YvIc7" href="https://app.cleanlab.ai/">Cleanlab Studio</a>, a user-friendly web app powered by our data-centric ML algorithms.

Software Engineer (Backend)

Software Engineer (Backend)
Location: San Francisco or Remote

Cleanlab’s mission is to democratize safe, trustworthy, and reliable AI. We believe the most promising path to such AI follows a data-centric approach. We build open-source algorithms and no-code SaaS solutions based on our research to help individuals and teams systematically and algorithmically curate high-quality datasets, which enables AI systems to train reliably on real-world messy and error-prone data.

The role
As a backend software engineer at Cleanlab, you will be responsible for building the backend APIs that power Cleanlab Studio, a user-friendly web app powered by our data-centric ML algorithms.

What you might work on
Designing and implementing backend features to support data visualization, interpretation, editing, and correction
Optimizing code for speed, scalability, and reliability
Ideating and prototyping novel product features enabled by our research
Collaborating with our data scientists and machine learning engineers to integrate feedback
Our backend tech stack includes Python, Flask, and Postgres.

What we’re looking for
Track record of shipping high-quality code in challenging projects
Exceptional programming skills
Ability to thrive in a fast-paced environment, navigate ambiguity, and adapt to changing priorities
Cleanlab strives to be a place where high-potential individuals come together to build something great. We value grit and the ability to learn quickly as much as skill and experience.

Our software engineering jobs have no hard requirements (like years of industry work experience, or even experience with the programming languages we use). Instead, we evaluate each application individually and consider any aspects that might stand out. Do you have some amazing open-source contributions? Did you write an impactful paper? Did you do some amazing work at a past job?

If you’re a great hacker, you believe in our mission, and you identify with our culture, we encourage you to apply!

How to apply
Apply here: https://cleanlab.ai/apply
Benefits
Working at Cleanlab is awesome! Beyond the opportunity to work at a well-funded AI startup with an incredible, friendly founding team of MIT graduates, all full-time employees receive the following:

Annual travel stipend
Travel enhances our empathy with different cultures and enables us to work together more effectively. It’s how we grow and learn: traveling is an essential part of what makes us human. At Cleanlab, every two months you will receive a reimbursable travel benefit. This is a unique benefit that lets you work from Paris for a week in February, then take a backpacking trip in the Andes for a weekend in March.
Premium health insurance (+ dental and vision)
We provide a fantastic $4 (we cover the rest) health insurance option. We also provide a $0 deductible 100% coverage premium health care option for those who prefer the best health insurance.
Professional development stipend to keep up with the latest innovations in ML and software.
Competitive salary (+ equity offering for certain roles), with regular opportunities for a raise if things are going well.
Relocation bonus to move to San Francisco
The compensation range for this role is $140,000 to $200,000. The final offer details are determined by several factors including candidate experience/expertise and may vary from the pay range provided.

About us
Prior to Cleanlab, our founders (3 ML PhDs from MIT) worked at OpenAI, Google, Microsoft, Amazon, AWS, Facebook AI Research (FAIR), Dropbox, Oculus, Palantir, NASA, General Electric, MIT Lincoln Laboratory, MIT, Harvard, and Stanford – at every place we worked we repeatedly encountered the same issue – AI solutions failed to work reliably on real-world, human-centric data due to label errors and poor data quality. So, we spent eight years of PhD research at MIT inventing a new field to solve this problem and after successful pilots with world-leading organizations, Cleanlab emerged.

Everything we do at Cleanlab is guided by our north star – to improve the world’s ML data more easily and quicker than any other solution – enabling AI systems to train more reliably on real-world, messy, error-prone data. We develop next-generation data-centric AI, open-source algorithms and provide no-code SaaS enterprise solutions to help individuals and teams at companies (across all industries) diagnose/fix issues in their datasets and produce more reliable ML models by providing clean labels for training.

While many companies can help store/manage data or develop ML models, there exist few solutions today to improve the quality of existing data, which is the core asset of the modern enterprise. This is where you come in. At Cleanlab, you’ll be able to take ownership of critical projects that pioneer the future of data-centric AI.

We are a hybrid company, with over half of our team (and office) located in San Francisco.

Read about the Cleanlab team here.
Read how Cleanlab went from MIT PhD research to tech used by Amazon, Google, etc here.
See what Google, Tencent, and other Cleanlab users think here.

We are willing to sponsor visas for the right candidate

Anton Relin

Tushar Jain

Abhishekh Sarvepalli

About usHarmonic is the startup discovery engine. We believe in innovation, entrepreneurs, and efficient capital markets. It pains us to see great startup opportunities consistently go undiscovered. So, we dedicated ourselves to mapping out the startup landscape and building the index and tools that ensure the most promising founders get found and funded.The world's largest and most prolific venture capital firms rely on us to find and invest in the next Google, AirBnB, Uber, Stripe, and Anduril. We play a crucial part in ensuring hundreds of billions of dollars get routed efficiently and that the innovations the world would most benefit from materialize.We’ve been growing steadily and need passionate driven people to help us get to the next level. If you want to work in a high-growth environment with some of the most talented folks on the planet and resonate with <a target="_blank" rel="noopener noreferrer" class="c-link" href="https://www.harmonic.ai/careers">our values</a>, read on.

Harmonic

Harmonic is using data and AI to map the world of startups. When companies are first formed, they’re invisible to the world. We’ve created the only complete startup database, enabling the right investments to reach the right entrepreneurs at the right moment. We cover founders who’ve just filed for incorporation to scaleups hiring their go-public CFO, all in real-time with rich firmographic, team info, and time-series data.We're looking a Staff Data Scientist to own our insights layer and build models and algorithms to generate first-party data.

Staff AI/ML Engineer

URL:https://boards.greenhouse.io/harmonic/jobs/4393840005
Apply Now
Staff Data Scientist
(View all jobs)
Brooklyn, New York
About Us

Harmonic is using data and AI to map the world of startups. When companies are first formed, they’re invisible to the world. We’ve created the only complete startup database, enabling the right investments to reach the right entrepreneurs at the right moment. We cover founders who’ve just filed for incorporation to scaleups hiring their go-public CFO, all in real-time with rich firmographic, team info, and time-series data.

Hundreds of venture teams have become data-driven and deployed their dollars more effectively thanks to Harmonic. Firms like Accel, NEA, Brex, Notion, and Google Ventures use Harmonic to connect startups with the capital and resources they need to drive growth. We’re backed by some of the best investors - Craft, Sozo, Floodgate, and several others, all of whom started as customers first.

We believe your ability to pick up new skills, excitement for personal growth, and passion for professional development are more important than where you are today. We invite you to reach out if you’re driven, curious, optimistic, and passionate about mastering your craft!

What we value:

Being customer-obsessed: At the start of each two-week sprint, we commit to our deliverables, focusing on customer impact and fulfilling commitments. Expect an environment of high personal accountability.
Continuous self-improvement: We prioritize growth and feedback, celebrating wins & achievements while focusing on how we can strive to be even better next time. We exchange regular feedback and hold quarterly sessions to discuss each other's strengths and areas for growth, driving our development. We index heavily on introspection, openness to feedback, and direct communication.
“Get shit done” attitudes: Even when things are uncertain, all of our team members excel at pushing projects ahead, asking the right questions, and overcoming obstacles to keep things moving. You understand the importance of balancing speed and quality, and you excel at communicating what can be realistically achieved given the circumstances.

Who you are:

Inquisitive: What kind of topics pique your interest? What keeps you up late at night? What kind of problems do you like to solve?
Accountable: Do you take psychological ownership of your work? What are your action steps when things don’t go according to plan? Can we count on your word?
Engaged: How active are you in accomplishing your personal and professional goals? Are you proactive about identifying roadblocks? What do you do when you see something that isn’t working?

If you are curious about the team, here’s more information:

Explore Working with Sang to understand decision-making processes related to the engineering function.
Explore Team Page to get acquainted with us. We're an exceptionally collaborative and engaged group, deeply committed to our shared cultural values.

Specifically, you will:

Own our insights layer: build models and algorithms to generate first-party data. This will include using statistical and machine learning techniques, including LLMs, to generate derived insights as well as determine accurate values from error-prone sources (e.g. headcount information)
Develop data products that improve the discoverability of startups in our database. Create and continually improve the similarity, relevance, and tagging algorithms that power our search engine.
Use your knowledge and creativity to extract as much value out of our data as possible. Make us the most valuable and useful source of information on startups.
Oversee general maintenance and health of data pipelines to ensure accurate and efficient transformations of our data.
Collaborate with the team to devise product goals, outline milestones, and execute plans, achieving this with minimal guidance.

Role requirements:

7+ years in Data Science or Data Engineering, or 5+ years industry experience + PhD
Fluency in Python and SQL
Experience with backend libraries and tools like dbt and dagster, familiarity with web servers, and comfort with large data sets.
Ability to work 3 times/week in our Brooklyn (Williamsburg) office.
Proven track record of shipping major projects for a data-centric startup.

Compensat:

$185K - $250K Salary + Equity (flexible depending on the level)

Our stack

The Process

Our goal in hiring is to make sure we click on both sides. We’re all about saving time and not beating around the bush. If it’s not looking like a match, we’re upfront and quick to say so, keeping things honest and moving smoothly for everyone involved.

We despise the typical software engineering interview process because it does not align with our day-to-day work. We structured our interview process around pragmatism. Expect us to ask questions closely aligned with the work we expect you to do.

Here’s our interview process:

(30 mins) Introduction Chat: Let's discuss whether Harmonic is the right place for you. We'll review your experience and allocate time for any questions you may have
(30 mins) Hiring Manager Call: Here we focus on accountability, and how much personal ownership one takes of their work.
(Max 5 hours) Take-Home Exercise: We will send you a description of one of our current company challenges and ask you to come up with a creative solution.
(45 minutes each) Team interview: Meet with a member of our Product team to focus on how you would collaborate, and another member of our Engineering team to go over your take-home & conduct a technical assessment.
(2.5 hours) Engineering Jam Session: Detailed discussion of the take-home and digging in deeper to measure technical skills. This will involve coding with 2-3 engineers on our team.
(Async) Reference Checks
(In person) Dinner/Lunch: Get to know Max, our CEO, over dinner! We can only get to know each other so much through video calls. We believe this is a critical hire and believe this investment is necessary. Flight and housing (if needed) are covered.
Benefits*
🩺  Top of the line health, dental and vision insurance, with 100% premium covered
📈  401k matching
🌴  Unlimited vacation and sick leave
🌍  Offices in NYC, SF, & LA
Read about our company culture
*For full-time employees only
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3 days a week in person in our NYC office (Williamsburg)

Qingchen Wang, Ph.D.

Hi! We're Extend, and we're helping companies deploy in-house AI agents for processing unstructured data. Extend is used in production at companies like Brex, Opendoor, Checkr, Vendr, and more. Our customers use our platform to build, deploy, and monitor intelligent data processing agents to turn their mountains of unstructured data (documents, PDFs, emails, images) → insights, customer NPS, operational efficiency, or new product initiatives.We're powering mission-critical data processing at companies where if we get things wrong, there are real world impacts (e.g. missed payments, people can't move into homes on time).Here's a few of the complex technical problems we're working on:<ul><li>How do we enable enterprises to deploy AI agents into production with confidence?</li><li>How do we handle never before seen edge cases in customer data?</li><li>How do we build a self-correcting system that automatically gets better over time?</li><li>How do we enable non-technical domain experts to train AI agents with their expertise &amp; business logic?</li><li>How do we help customers make tradeoffs between latency, cost, and performance?</li><li>How do we build reliable systems that can process large data streams in real-time?</li></ul>

Co-Founder & CTO

Extend (YC W23)

Extend is enabling enterprises to deploy in-house AI agents for processing unstructured data. As an AI Engineer at Extend, you’ll design novel techniques, systems, and human ↔ AI interfaces for building LLM agents that operate on complex data streams. We’re looking to hire engineers who think creatively about problems, keep up to date on the latest in AI research, push for real-world customer impact (not only theory), and are excited about empowering organizations with AI.We're powering mission-critical data processing at companies where if we get things wrong, there are real world impacts (e.g. missed payments, people can't move into homes on time).Here's a few of the complex problems you’ll be working on:<ul><li>How do we build a self-correcting system that automatically gets better over time?</li><li>How do we enable non-technical domain experts to train AI agents with their expertise &amp; business logic?</li><li>How do we deploy non-deterministic AI into mission-critical flows?</li><li>How do we help customers make tradeoffs between latency, cost, and performance?</li></ul>

Senior AI Engineer

About the role
Extend is enabling enterprises to deploy in-house AI agents for processing unstructured data. As an AI Engineer at Extend, you’ll design novel techniques, systems, and human ↔ AI interfaces for building LLM agents that operate on complex data streams.

We’re looking to hire engineers who think creatively about problems, keep up to date on the latest in AI research, push for real-world customer impact (not only theory), and are excited about empowering organizations with AI.

IMPACT
We're powering mission-critical data processing at companies where if we get things wrong, there are real world impacts (e.g. missed payments, people can't move into homes on time).

Here's a few of the complex problems you’ll be working on:

How do we build a self-correcting system that automatically gets better over time?
How do we enable non-technical domain experts to train AI agents with their expertise & business logic?
How do we deploy non-deterministic AI into mission-critical flows?
How do we help customers make tradeoffs between latency, cost, and performance?
ROLE
Design novel LLM techniques for increasing the complexity of use cases and data streams that Extend can be applied to
Monitor existing agents in production, understand what’s working well (and what isn’t), and run experiments to solve those issues
Implement the best human ↔ AI interfaces for designing data processing agents. We are building a new territory of UX that previously did not exist. It’s up to us to discover and implement new patterns that work for our users.
Have complete ownership over the work you do — as a founding team member, you’ll have the opportunity to truly own large areas of product and engineering and have direct relationship with customers.
Work directly with the CEO, CTO, and other founding members and help build out our team.
About Extend
Hi! We're Extend, and we're helping companies deploy in-house AI agents for processing unstructured data. Extend is used in production at companies like Brex, Opendoor, Checkr, Vendr, and more. Our customers use our platform to build, deploy, and monitor intelligent data processing agents to turn their mountains of unstructured data (documents, PDFs, emails, images) → insights, customer NPS, operational efficiency, or new product initiatives.

We're powering mission-critical data processing at companies where if we get things wrong, there are real world impacts (e.g. missed payments, people can't move into homes on time).

Here's a few of the complex technical problems we're working on:

How do we enable enterprises to deploy AI agents into production with confidence?
How do we handle never before seen edge cases in customer data?
How do we build a self-correcting system that automatically gets better over time?
How do we enable non-technical domain experts to train AI agents with their expertise & business logic?
How do we help customers make tradeoffs between latency, cost, and performance?
How do we build reliable systems that can process large data streams in real-time?
TEAM
We're a small team of 5 that's fully in-person in NYC. Our backers include Homebrew, Innovation Endeavors, Character, and angels from OpenAI, Brex, Airbnb, Newfront, and more.

Mana is a research lab building an artificially intelligent investor. We sell contracts to financial firms, private equity and wealth management firms, as well as VCs. We help any firm looking to optimize their workflows with AI. We are semi in stealth, but typically have very large contracts right.As we build, we are paving a path to what we hope will lead to a future with AI/automated investing.

Co-Founder & CEO

Mana

You will build the machine learning systems that power our general artificial intelligence for capital allocation. We are looking for researchers who want to discover elegant deep learning concepts and then put them into production as solutions to high-stakes, real-world problems.

Applied AI Researcher

Visa sponsorship available to exceptional candidates that don't have work rights in the US

Trace Ohrt

What we do Our mission is to empower building materials suppliers with great technology. There are over $1,000,000,000,000 of building materials bought in the US every year, and many of these transactions happen in on-prem point-of-sale systems. We want to bring these transactions online, enabling better experiences for contractors and homeowners alike.What we stand for ⭐️The values we hold most dear are learning through feedback and experimentation, enjoying our time together, truly empathizing with clients (we've worked at paint stores &amp; lumber yards!), building a diverse team, and driving to achieve as fast as we can.How we've fundraised 💰We've raised $18m across three rounds:<ol><li>A $2m pre-seed led by <a target="_blank" rel="noopener noreferrer nofollow" href="https://www.bvp.com/team/kent-bennett">Kent Bennett</a> at <a target="_blank" rel="noopener noreferrer nofollow" href="https://www.bvp.com/">Bessemer</a> with participation from Plug &amp; Play, Quiet Capital, and Sequoia.</li><li>A $5m seed led by <a target="_blank" rel="noopener noreferrer nofollow" href="https://www.crv.com/team/caitlin-bolnick-rellas">Caitlin Bolnick Rellas</a> at <a target="_blank" rel="noopener noreferrer nofollow" href="https://www.crv.com/">CRV</a>.</li><li>An $11m series A led again by Bessemer and CRV.</li></ol>

Rundoo

This role is focused on empowering building materials suppliers with innovative technology to bring transactions online and enhance experiences for contractors and homeowners. The ideal candidate will make significant contributions to the software used by clients, introduce systems to improve team velocity, set and enforce engineering quality standards, mentor teammates, and collaborate with product and design teams to define project goals.

Backend Engineer (Go)

General
What we do 🪵

Our mission is to empower building materials suppliers with great technology. There are over $1,000,000,000,000 of building materials bought in the US every year, and many of these transactions happen in on-prem point-of-sale systems. We want to bring these transactions online, enabling better experiences for contractors and homeowners alike.

This Role
What you'll achieve with us 🥇

You'll make significant individual contributions that get used instantly & heavily by our clients who depend on our software to run their businesses.

You'll leverage your orthogonal expertise to introduce abstractions and systems that improve the team's velocity.

You'll raise the bar for engineering quality by setting and enforcing standards.

You'll mentor teammates to help them grow as architects & engineers.

You'll work closely with product & design teammates and our clients to collectively define what we're building.

Requirements ✅

You collaborate well with engineering teammates and cross-functionally—especially working through natural tension with designers and product managers.

You give positive & constructive in-the-moment feedback to your teammates and enjoy receiving the same.

You're excited to work at least a couple days a week in-person at our office in Redwood City.

You have worked as a software engineer for 5+ years.

You have written production backend software using Go.

Icing on the cake 🎂

You have worked in a fast-paced startup environment.

You have written frontend software using React and TypeScript.

You have familiarity with construction or building materials.

Interview process

Intro Call (15 min): Getting to know each other and aligning on expectations for the role with Nick.

Technical Screen (1 hour): Working through debugging and coding challenges with Andrew.

Onsite @ Redwood City HQ (~5 hours):

Walk (45 min): Diving into the business with Nick.

System Design (1 hour): Designing a system to address an abstract problem with George.

Lunch (45 min): Breaking bread with the team.

Product Collaboration (1 hour): Going back & forth on a PRD with Vidhan.

Culture (30 min): Reflecting on past experiences with Emmie.

Q&A (30 min): Answering your questions with Andrew.

Who we are
In alphabetical order:

Adam (Territory Account Executive): studied Communications at UConn (Go Huskies!) and worked as an AE at a large cloud software company (Box); a frequent at concerts around the greater NYC area in his spare time 🫡

Amanda (Recruiting & Operations); studied marketing at De La Salle University; worked in recruiting at a few startups; loves SCUBA diving! 🌊

Andrew (CTO): studied computer science & humanities at Stanford; worked as a software engineer and head of engineering at Apple & Anova; danced with the SF ballet (where he met his wife)! 🩰

Gemma (Andrew's Bernedoodle): *fiercely protecting Andrew* 🐶

Andy (Territory Account Executive): studied Business Management at Oklahoma State University (Go Pokes); worked as an AE for large tech like Cisco System and small startups BeckTech and TrackStreet; do you need a 4th? ⛳️🏌🏼‍♂️

Brian (Engineering): studied computer science & applied math at NJIT and UC Davis; worked as an engineer at Google, Snap, and Common Networks; LoL player and Earthquakes fan ⚽

Luna (Brian's chocolate lab): *looking longingly at YB* 🦮

Claire (Client Success Lead): studied History at Dartmouth College; worked in Account Management and Customer Success at Yahoo, Outlier AI, and Persona; loves following women's sports and studying architecture 🏑🏡

Clara (Territory Account Executive): studied Literature at University College London; worked in GTM strategy for a feminine health tech startup in Paris and then came to the bay to work in sales for Verkada; often seen doing a headstand 🧘‍♀️

Daniel (Territory Account Executive: studied Biology at University of Washington, worked in sales in pharmaceuticals at Eli Lilly and in FinTech at PitchBook; often found playing volleyball 🏐

Emmie (Engineering): studied math & computer science at Stanford; worked as a software engineer at Flexport; loves confetti cake 🧁 and almond croissants 🥐

George (Engineering): studied computer science at Stanford; worked as a software engineer at Facebook; exclusively reacts on Slack with the shaka! 🤙

Joe (Director of Growth): studied math & computer science at Stanford; worked as a consultant at Bain & Company; has been pulled over for speeding on a bicycle but never in a car 🚴‍♂️

Jonathan (Implementation): studied Linguistics at Cedarville University; worked in SaaS implementation for startup Tekion; has flown over 100k miles in the last year 🛫

Jordan (Engineering intern): studying computer engineering at the University of Waterloo; worked at Rivian, IBM, and elsewhere; plays the saxophone professionally 🎷

Kyle (Territory Account Executive): Studied Anthropology and History at UNCW; Has been a seller for companies big and small, mostly in the Software space. Is self-taught in catching snakes barehanded🐍

Mango (Kyle's corgi): *demanding pets from everyone he meets* 🐾🥭

Lej (Implementation) working directly in the field of software for the last three years helping entrepreneurs and start-ups alike. Aspires to create a smart home environment similar to the one depicted in the 1999 Disney movie "Smart House."🎮

Matt (Territory Account Executive): studied history at Northwestern; taught middle school in Chicago (hardest job ever), more recently worked in sales and general management at a fishing tackle company (Catch Co.); former competitive angler in college (bass fishing 🎣)

Max (Product Manager): studied neuroscience at Dartmouth; worked as a consultant at Bain & Company and as a PM for RabbitHole; has broken his neck exactly one time (and coincidentally has tried parkour exactly one time 🤸‍♀️)

Nick (CEO): studied math & computer science at Stanford; worked as a trader at Bridgewater & Citadel and as a PM at Google & Enigma; distantly related to the founder of the Hershey company 🍫

YB (Nick's Belgian Malinois): *looking longingly at Luna* 🐕

Noah (Product Designer): studied Art Practice at Stanford; worked as a Product Designer at several startups in consumer social; has too many hobbies including volleyball, pool, painting, gamedev, birdwatching, music, cooking, trivia, and sumo. 🎱

Rae (Territory Account Executive): Studied Business Management at University of Colorado; Worked as an account executive at Sumup; likely the only Colorado native who doesn't ski or snowboard. 💃🏻

Santiago (Engineering): studied computer engineering at University of Waterloo; worked as SWE intern at The Cooperators, Inflight, BitBakery, Replicant; played lots of soccer, loves rap and r&b 🎧

Tyler (Client Success): studied general education and tech at Cabrillo College; worked as a system administrator for a short time and at a paint store (Kings paint!!!) for eight years, manager for two; likes to play most video games, currently playing Diablo 4. 🕹

Umer (Engineering): studied computer science at National University of Singapore; worked as a SWE intern at Visa and an NLP chatbot startup; has an identical twin! 👯‍♂️

Vidhan (Product): studied Biomedical Engineering and Econ at Duke; Worked as a PM at Hinge Health and BuildZoom. Previously at Zenefits. Founder Urova Medical; 🍪

Waffle (Vidhan's Labradoodle): Stealing whatever food can be found 🐶

Zach (Design): studied product design at Stanford; worked in design at a few startups; currently wearing socks with cocktails on them! 🍹

What we stand for ⭐️

The values we hold most dear are learning through feedback and experimentation, enjoying our time together, truly empathizing with clients (we've worked at paint stores & lumber yards!), building a diverse team, and driving to achieve as fast as we can.

How we've fundraised 💰

We've raised $18m across three rounds:

A $2m pre-seed led by Kent Bennett at Bessemer with participation from Plug & Play, Quiet Capital, and Sequoia.

A $5m seed led by Caitlin Bolnick Rellas at CRV.

An $11m series A led again by Bessemer and CRV.

Benefits 🩺

Medical, vision, and dental insurance with 100% premiums covered for you, 50% for dependents (~$5-6k/yr) 🏥🥸🦷

Daily lunch (~$4k/yr) 🥘

Learning materials and Coursera courses (~$1k/yr) 📚

Unlimited audiobooks via our team subscription to Libro ($500/yr) 🎧

Gym membership! (~$1200/yr) 💪

Unlimited PTO 🏖️

Betterment 401k 🏦

Dog-friendly office 🐶

And more! If you have ideas, let us know 🙂

Aniket Trivedi

At Palantir (NYSE: PLTR), we're helping the world's most important institutions use their data to solve their most urgent problems. Our software lets our customers integrate and analyze all of their data so they can answer questions that they couldn't before. From delivering disaster relief to building safer automobiles, we're honored to help make our partners better at their most important work. Together with our customers, we're building the future of national security, healthcare, energy, finance, manufacturing, and more. And we need bright minds from around the world to help us.

Palantir

Are you passionate about engineering quality, efficiency, and increasing the impact of engineers around you?Software Engineers at Palantir build software at scale to transform how organizations globally use data. As a Software Engineer on Developer Productivity, you’ll identify, develop, and drive investments to improve the velocity and quality of our engineering, as well as bolster the happiness and productivity of other developers.The role spans a spectrum of areas, such as build and software supply-chain systems, platform runtime environments, telemetry relating concurrency, memory/performance optimizations, and monitoring/alerting. Your primary users will be other developers at Palantir. They will be empowered with the software you develop to build capabilities used by research scientists, aerospace engineers, intelligence analysts, and economic forecasters in countries around the world. There will be opportunities to contribute to open source software, including projects maintained by others that we leverage. You’ll work autonomously within a community that will support and challenge you as you grow to become a strong technical contributor and engineering leader.The team is hiring for Frontend and Backend engineers.

Software Engineer - Developer Productivity (Palo Alto/NY)

3-4 days a week in the office. Relocation services are available to all new hires relocating 50+ miles to their new Palantir office of employment. Relocation support may be utilized for 12 months after the new hire's start date. After 12 months, relocation benefits will expire and unused benefits can no longer be used.

Dima Timofeev

We're looking for strong software engineering skills and experience productionizing code/models in cloud environments while maintaining the necessary infrastructure. You should be comfortable with large software systems. Experience working in MLOps: processing data, deploying and monitoring models, cloud infrastructure (AWS), Big Data stack, etc.We do not require deep knowledge of ML algorithms, but you must have previously worked on many ML and Data projects at companies (across their full life-cycle, not say just in Jupyter).

Co-founder and CTO

MLOps Engineer

URL:https://cleanlab.ai/careers/ml-engineer/
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Senior ML Engineer

Location: San Francisco (flexible/hybrid)

At Cleanlab you’ll get to

Pioneer novel software systems for data-centric AI. Our tools enable data scientists/engineers (across all industries) to effectively diagnose/fix issues in their datasets, thus improving the quality of their business’s core asset.

Discover how to best leverage new Generative AI advances for tools that automatically find & fix issues in datasets. The north star of our company is to use AI to increase the value of Data.

Work with text, structured/tabular, image/video datasets from companies across diverse industries, and set up large-scale modeling infrastructure at a dynamic startup (0 to 1).

What we’re looking for

Strong software engineering skills and experience productionizing code/models in cloud environments while maintaining the necessary infrastructure. You should be comfortable with large software systems.

Experience in MLOps: processing data, deploying and monitoring models, setting up the necessary infrastructure for Data/AI projects.

Up to date on the latest advances in Generative AI (LLMs, LVMs)

Responsibilities
Spin up cloud infrastructure for ML projects spanning text, image, and structured/tabular datasets.
Work on large-scale Data/AI projects with Cleanlab enterprise customers, from inception to production.
Work as individual contributor tech lead on a ML team of around 5.
Innovate on new algorithmic techniques to improve a dataset, leveraging the newest Foundation model advances.
Qualifications

This is a senior role! Candidates must have at least 5+ years work experience in ML. Schoolwork or general data science work does not count, you should have tackled hard MLOps challenges at companies dealing with massive datasets, reliable model serving, cloud infrastructure, etc.

Python (pandas, scikit-learn, numpy, Jupyter)
PyTorch/PyTorch Lightning, Hugging Face
Relational databases
AWS
Docker
Git
CI/Testing, e.g. Jenkins

Bonus:

PhD in Machine Learning
Strong research publications or open-source contributions
Sagemaker, MLflow, Ray
ELT tools and data cleaning tools
Cleanlab or other data-centric AI tools
LangChain and LLMOps stack
Benefits

Working at Cleanlab is awesome! Beyond the opportunity to work at a well-funded AI startup with an incredible, friendly founding team of MIT graduates, all full-time employees receive the following:

Annual travel stipend
Travel enhances our empathy with different cultures and enables us to work together more effectively. It’s how we grow and learn: traveling is an essential part of what makes us human. At Cleanlab, every two months you will receive a reimbursable travel benefit. This is a unique benefit that lets you work from Paris for a week in February, then take a backpacking trip in the Andes for a weekend in March.
Premium health insurance (+ dental and vision)
We provide a fantastic $4 (we cover the rest) health insurance option. We also provide a $0 deductible 100% coverage premium health care option for those who prefer the best health insurance.
Stipend for attending conferences to keep up with the latest innovations in ML and software.
Competitive salary (+ equity offering for certain roles), with regular opportunities for a raise if things are going well.

The compensation range for this role is $180,000 to $220,000. The final offer details are determined by several factors including candidate experience/expertise and may vary from the pay range provided.

About Us

Prior to Cleanlab, our founders (3 ML PhDs from MIT) worked at OpenAI, Google, Microsoft, Amazon, AWS, Facebook AI Research (FAIR), Dropbox, Oculus, Palantir, NASA, General Electric, MIT Lincoln Laboratory, MIT, Harvard, and Stanford – at every place we worked we repeatedly encountered the same issue – AI solutions failed to work reliably on real-world, human-centric data due to label errors and poor data quality. So, we spent eight years of PhD research at MIT inventing a new field to solve this problem and after successful pilots with world-leading organizations, Cleanlab emerged.

Everything we do at Cleanlab is guided by our north star – to improve the world’s ML data more easily and quicker than any other solution – enabling AI systems to train more reliably on real-world, messy, error-prone data. We develop next-generation data-centric AI, open-source algorithms and provide no-code SaaS enterprise solutions to help individuals and teams at companies (across all industries) diagnose/fix issues in their datasets and produce more reliable ML models by providing clean labels for training.

While many companies can help store/manage data or develop ML models, there exist few solutions today to improve the quality of existing data, which is the core asset of the modern enterprise. This is where you come in. At Cleanlab, you’ll be able to take ownership of critical projects that pioneer the future of data-centric AI.

We are a hybrid company, with over half of our team (and office) located in San Francisco.

Read about the Cleanlab team here.
Read how Cleanlab went from MIT PhD research to tech used by Amazon, Google, etc here.
See what Google, Tencent, and other Cleanlab users think here.
How to Apply
Apply here: https://cleanlab.ai/apply
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Data and Tech Consulting
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Financial Services and Insurance
E-Commerce and Retail
Manufacturing and Agriculture
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Data Entry, Management, and Curation
Foundation and Large Language Models
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Data Annotation and Crowdsourcing
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We are a hybrid company, we need candidates who can be in office at least a couple days each week. Office is in Mission District of SF

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