
The data layer for physical AI
About us
Encord is the universal data layer for AI that helps 300+ AI teams train and run models on the right data. Our platform indexes, curates, annotates, and evaluates data across the full AI lifecycle, from development through production. Trusted by Woven by Toyota, AXA, UiPath, Zipline, and more.
We're an ambitious team of 100+ working at the frontier of AI and have raised $60M in Series C funding from Wellington Management, CRV, Next47 and Y Combinator.
The role
We are looking for an experienced Applied AI Engineer to join our team and help us build and scale cutting-edge machine learning and computer vision solutions that power real AI workflows. You'll work hands-on across the full ML lifecycle — from experimenting with the latest models and techniques to integrating them into a production platform used by hundreds of AI teams worldwide.
This is a highly collaborative role where you'll partner closely with our product engineering and human data teams to turn complex algorithmic ideas into reliable, scalable features that customers love. Our work is at the cutting edge of computer vision and deep learning, which also includes working on solving unsolved problems within those fields.
If you're someone who thrives at the intersection of strong ML fundamentals and practical engineering, and wants to see their work make a direct impact at scale — this is the role for you.
What you'll do
Experiment with and adapt the latest ML technologies to fit into our existing tech stack
Solve idiosyncratic statistical, geometric, and engineering problems
Work closely with a full-stack tech team to assist implementation of research solutions into the product
Contribute to hiring additional talent to our rapidly growing team
Work with a broad tech stack (e.g. ReactJS, Python, REST & GraphQL, OpenCV, PyTorch, GCP, AWS & CUDA, Kubernetes) and the cutting edge of computer vision and deep learning
Who we're looking for
Hands-on and experimental — you're comfortable executing on projects end-to-end, running tests, and iterating based on what the data tells you
Collaborative by nature — you work closely with engineering and product teams to turn complex algorithmic ideas into reliable, scalable features
Driven to solve hard problems — you thrive at the intersection of strong ML fundamentals and practical engineering
Bonus: you've led or contributed to applied research teams and have relevant publications to show for it
Experience requirements
3+ years of experience in machine learning engineering, with concrete examples of models or systems you've built and shipped
Strong experience in Python and ML libraries such as OpenCV, PyTorch, TensorFlow, Fast.ai, and Keras
Strong foundation in mathematical programming, algorithmic problem solving, and applied machine learning
Bonus: experience in the AI/ML ecosystem and familiarity with computer vision
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: 4–5 days/week in our newly launched North Beach loft office
Flexible PTO to fully recharge
18 paid vacation days in the U.S. plus federal holidays
Annual learning & development budget
Comprehensive health, dental, and vision coverage
Frequent travel opportunities across the U.S., London, and Europe
Bi-annual company offsites, twice-weekly team lunches, and monthly socials
At Encord, we're building the AI infrastructure of the future. Today, the biggest challenge companies face in getting an AI product to market is actually not half as glamorous as it may seem: it's all about data quality. In fact, the success of any AI application today relies on the quality of a model's training data — and for 95% of teams, this essential step is both the most costly and the most time-consuming.
As ex-computer scientists, physicists, and quants, we felt first-hand how the lack of tools to prepare quality training data was impeding the progress of building AI. AI today is what the early days of computing or the internet were like, where the potential of the technology is clear, but the tools and processes surrounding it are still primitive, preventing the next generation of applications. This is why we started Encord.
We’re a team of 60 working at the cutting edge of computer vision and deep learning, backed by top investors, including CRV and Y Combinator, leading industry executives like Luc Vincent, former VP of AI at Meta, and other prominent leaders in AI. We are one the fastest growing companies in our space, and consistently rated as the best tool in the market by our customers.