Quant Developer in AI

About us

We're solving AI's hardest problem: alignment.

Encord is the data layer for Physical AI and enterprise, serving as core infrastructure for 300+ of the world's leading AI teams, including Woven by Toyota, Hitachi, Skydio, AbbVie and Dyna, Walden and Agility Robotics. From autonomous vehicles and robotics to sports and healthcare, we're solving AI's hardest problem: turning complex, real-world data into production-ready intelligent systems.

We're a team of founders, scientists, quants, researchers, and former Olympians, who’ve helped build some of the most successful companies in Silicon Valley, and alumni of MIT, Stanford, UC Berkeley, Oxford, Cambridge, and Imperial. We’ve raised $110M from legendary technology investors, early backers of companies like Databricks, ElevenLabs and Vercel, and we’re growing at an extraordinary pace.

We're looking for exceptional people who want to help build a category-defining company, operating with high urgency and taking real ownership to help shape the future of AI.

Quant Developer in AI

You're a quant developer. You've built high-performance systems that process billions of events per day in real-time, and you care deeply about consistency, correctness and performance. Now you want to build in AI

This is your chance. Encord is a scale-up serving the frontier of physical AI and robotics, the largest technological revolution in history, where what you build ships fast and you own it. Help us build the AI data platform for the future of robotics.

The role

You know how to build systems that are fast and correct under pressure. The hardest problems in AI right now are data problems: distributed, data-intensive systems that have to stay correct and performant at scale.

You will join the Foundations team, who build the data systems that enable frontier robotics labs to generate, understand, train, and test on massive volumes of robotics data. We don’t just react to an order book tick - you will need to handle large 3D scenes, hour-long videos, LIDAR point clouds, and ML inference, all under tight performance and operational budgets.

Why now? A year ago we were a team of 100; now we're over 180 and still accelerating. You'll work directly with a high-bar team, take on high-stakes problems, and help shape where the platform goes next.

What you'll do

• Design, build, deploy and own data systems processing petabytes of data across billions of items, from design and architectural decisions all the way to deployment, monitoring and measuring impact

• Build robust distributed systems and reason carefully about how they fail and how they behave under load

• Design performant protocols and APIs, and tackle complex domains and immense scale with correct and pragmatic solutions, moving extremely fast while maintaining engineering quality.

• Build as part of a high-performing team, contribute your knowledge and experience to others.

Who you are

• You have personally developed and maintained systems from scratch, and know what trade-offs are involved in building reliable, performant software at speed. You will have excelled at something demanding, and can show that your good technical decisions day after day compounded into a competitive edge.

• You may not have AI or ML experience, and that's fine: you are an incredibly fast and curious learner. You can pick up a new topic and quickly become an expert by being ego-less in asking the right questions, and rigorous in performing experiments that propel you up the learning curve.

• You excel under pressure and uncertainty. You don’t let up the pace, you attack the heart of the problem, and you repeatedly make the right tradeoffs.

• You deeply care about the systems you build. You take pride in having thought through the failure modes, shipping readable, bulletproof code, and delivering today instead of next week.

• You enjoy being a member of a high-performing team. You contribute your best work and help others contribute their best. You'll always lend a helping hand when needed and level up those around you.

Experience requirements

• 1-5+ years building and operating serious institutional-scale systems.

• Fluency in Python or Typescript and a deep understanding of a least one of Rust, C++, Java or Golang.

• Solid core CS knowledge in data structures and algorithms, distributed systems concepts (databases, replication, partitioning, queuing, caching) and how they behave under load

• Experience owning services in production and improving quality through code reviews, testing, rollout and monitoring

• Experience at a trading firm, market maker, hedge fund or exchange is a plus: trading systems, market data pipelines, tick or time-series stores, risk engines, ML/QR research pipelines, are all relevant to what we build. Experience with large data migrations or re-architecture projects is a plus.

Why Encord

• Competitive salary, commission, and meaningful equity in a high-growth startup

• Clear, accelerated growth opportunities as the company scales rapidly

• Strong in-person culture: 4 days/week

• Daily team lunches & dinners

• Annual learning & development budget

• Comprehensive health, dental, and vision coverage

• US employees: 18 paid vacation days plus US public holidays

• UK employees: 25 paid vacation days plus UK public holidays

• Frequent travel opportunities across the U.S., London, and Europe

• Bi-annual company offsites & monthly socials

Operating principles

High agency

You see something broken, you fix it or find the person who can. We celebrate the people who solve 90% of a problem before anyone asks.

Build with care & urgency

We bear-hug the customer. Former founders and people from fast-moving, high-stakes environments thrive here.

Self-aware & hungry

We stay warm, self-aware, and genuinely hungry. We elevate our peers, and ego doesn't last long.

Invent in real time

We move toward the ambiguity. We’re pragmatic, resourceful, energized by the fact that there's no playbook.

If you're looking to do the most meaningful work of your career alongside people who push you to be better, we'd love to meet you.