Product Engineer, Encord
+ Equity & Commission
4-5 days a week in office
Data platform for AI training
Open for applications
Data platform for AI training
101-200 employees
Open for applications
+ Equity & Commission
4-5 days a week in office
101-200 employees
Company mission
To solve AI alignment by tackling the real bottleneck: data quality.
Role
Who you are
- If you have strong opinions about what good software looks and feels like — and the drive to make it happen — you'll fit right in
- You've seen and built a lot. You have personally developed and maintained multiple systems from scratch, and you know what trade-offs are involved in building reliable, performant software at speed
- You want your work to have a tangible outcome for people. You're not satisfied with building products that do not see the light of day
- You are a builder. You enjoy all aspects of building not only software but a complete product, and are comfortable moving across the stack when necessary
- You enjoy problem-solving and thinking from first principles, and are always ready to pick up new skills and build quickly
- You're happy to tackle problems without a predefined, clear definition or obvious solution, and are excited to have autonomy to make decisions as you go
- You understand that being a member of a high-performing team requires two things. 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
- Strong full-stack engineering experience, with a strong track record of shipping products you're proud of
- Deep fluency in at least one high-level language (we use Python and TypeScript, but we care more about depth than the specific language)
- Strong front-end skills — comfortable with building polished, responsive interfaces, ideally with React
- Familiarity with cloud infrastructure (GCP preferred) and containerised deployment (Kubernetes) is a plus
- Experience building at scale in a fast-paced startup or high-growth environment
- Exposure to machine learning workflows or ML infrastructure is a plus
What the job involves
- As a Product Engineer at Encord, you'll be embedded at the core of our product — owning features end-to-end, from the API design and backend systems all the way through to the UI that annotation teams, ML engineers, and compliance officers use every day. You won't be handed specs; you'll help write them
- We care deeply about product craft, technical excellence, and shipping things that genuinely matter to our clients
- Build scalable back-end systems and intuitive front-end interfaces — owning features from database schema to rendered UI
- Work with ML workflows — developing tooling for model evaluation, active learning, and automated quality pipelines
- Iterate rapidly on product and ship high-quality features at pace, maintaining strong CI/CD and testing practices throughout
- Work closely with customers, product, and design to understand problems deeply and deliver solutions that create real impact
- Contribute to shaping how the team works — our architecture decisions, engineering culture, and product direction are all open for input
- We are technology-agnostic at Encord and are not looking for experience across all of these — as long as you're open to learning, please apply:
- Backend: Python
- Frontend: TypeScript and React
- Deployment: Kubernetes
- Infrastructure: GCP
- Machine learning: PyTorch, CUDA, Ray
Salary benchmarks
Our take
It has become increasingly clear that the next generation of AI applications will be driven by data-centric approaches concentrated around training data creation, management, and evaluation. Crucial within this process is the annotation or 'labelling' of data. Traditionally, such annotation has been left to human workers, which has historically made this part of the process of AI development expensive, slow, and difficult to scale.
Encord offers a computer vision annotation platform that automates a number of manual labelling tasks. Its suite of tools is designed for collaboration across roles and teams, from domain-expert annotators to project managers and machine learning engineers. This allows companies to iterate 10x faster, and develop and deploy high performing models in less time whilst saving on annotation costs.
Demand is clearly there: since its launch in 2020, Encord has facilitated the annotation of more than 100 million frames and images and served customers in verticals such as medical imaging, smart cities, sports analytics and satellite imaging. Furthermore, usage is scaling rapidly, with the number of labels generated on the platform growing ~70% month-over-month.
Steph
Company Specialist at Welcome to the Jungle
Insights
Company
Funding (last 2 of 5 rounds)
Feb 2026
$60m
SERIES C
Aug 2024
$30m
SERIES B
Total funding: $107.2m
Company benefits
- Competitive salary, commission, and meaningful equity in a high-growth startup
- Strong in-person culture: 3–5 days/week in our London, SF, and NYC offices
- Flexible PTO to fully recharge
- Annual learning & development budget
- Frequent travel opportunities across the U.S., London, and Europe
- Bi-annual company offsites, twice-weekly team lunches, and monthly socials
- Company lunches twice a week
- Clear, accelerated growth opportunities as the company scales rapidly
Company HQ
North Beach, San Francisco
Leadership
Eric Landau
(CEO)With MScs from Harvard and Stanford, Eric spent 8+ years as a senior quant at DRW deploying ML at scale—before co-founding Encord to make data the core of AI development.
Ulrik Stig Hansen
(President)Ulrik spent 3+ years in Sales & Trading at J.P. Morgan and holds science master’s degrees from UCL and Imperial—before co-founding Encord to transform how AI handles data.
Share this job
View 2 more jobs at Encord