Product Engineer, Encord
Physical AI
+ Equity & Commission
4-5 days a week in office
Data platform for AI training
Be an early applicant
Data platform for AI training
101-200 employees
Be an early applicant
+ 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
- Experienced: you've seen a lot and built a lot — personally developed and maintained multiple systems from scratch, with a deep understanding of the trade-offs involved in building reliable, performant software at speed
- At home with challenging frontend work: you're comfortable rendering complex 3D scenes, working with spatial and sensor data, and optimising for browser performance
- Impact-driven: you want your work to have a tangible outcome for people and aren't satisfied by products that don't see the light of day
- A builder: you enjoy all aspects of building a complete product, are comfortable moving across the stack, and love problem-solving from first principles
- Comfortable with uncertainty: happy to tackle problems without a predefined solution, and excited to make decisions autonomously as you go
- A team player: you contribute your best work and actively help others do the same — you enjoy levelling up those around you
- Strong full-stack engineering experience, with a particular strength in complex, high-performance frontend work
- Experience with 3D rendering, WebGL, or similar technologies for visualising spatial/sensor data is a strong plus
- Proficiency in Python and/or TypeScript; experience with React a plus
- Familiarity with cloud infrastructure (GCP preferred) and containerised deployment (Kubernetes)
- Experience in robotics, autonomous vehicles, or Physical AI is a plus
What the job involves
- We're building tools for the full Physical AI data stack — from data acquisition, through ingestion and curation at scale, to 3D rendering, annotation, and verification. You'll solve problems of large-scale efficient data transfer and storage, complex domain modelling, applying the latest machine learning models, and squeezing performance out of web browsers
- You'll work with the biggest names in robotics and autonomous vehicles, and join a small, highly collaborative team at a crucial stage of accelerated development. You'll be a key driver of progress on a core part of our product, operating with a high degree of autonomy and crafting performant, reliable, and maintainable solutions at speed
- Build and maintain high-performance frontend experiences, including rendering complex 3D scenes with thousands of objects at smooth frame rates
- Work across the full stack — from backend data pipelines and storage systems to frontend visualisation and interaction
- Take end-to-end ownership of projects, from product and architectural decisions through to deployment, monitoring, and measuring user impact
- Work with visual, spatial, and sensor data to make sense of the physical world
- Tackle complex domains at massive scale using simple, well-crafted solutions
- Take initiative, be proactive in problem-solving, and continuously seek improvements
- Tech stack
- We are technology agnostic at Encord and 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