Robotics Systems Engineer

About us

At Encord, we're building the AI infrastructure of the future. The biggest challenge AI companies face today is not nearly as glamorous as the outside world may think: 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. For 95% of teams, this essential step is both the most costly, and the most time-consuming in getting their product to market.

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 are a team of 100+, working at the cutting edge of multimodal and visual AI. Encord is backed by top investors, including CRV, Y Combinator, and Next47, leading industry executives like Luc Vincent, former VP of AI at Meta, and other Bay Area AI leaders. We are one the fastest growing companies in our space, and consistently rated as the best product in the market by our customers.

The Role

We're building a robotics data collection operation from scratch — and we need someone to figure out how to make it work. There's no playbook. No inherited infrastructure. No one to tell you what to do next.
You'll own the entire stack: robot arms, sensors, VR rigs, data pipelines, quality systems, and customer delivery. You'll make decisions about what equipment to buy, how to set it up, and how to build pipelines that turn raw sensor streams into premium training data. When something breaks hardware or software you fix it. When we need a capability that doesn't exist, you build it.

This is a 0-to-1 role. If you need clear instructions, a defined scope, or someone to tell you what "good" looks like — this isn't for you. If you get energized by building something from nothing and figuring it out as you go, keep reading.

What You'll Do

- Build the hardware infrastructure - Set up and maintain robot arms, sensors, VR rigs, and cameras. Design workstation layouts. Keep systems calibrated and operational. When something breaks mid-shift, get us back online. When we scale from 10 to 50 stations, figure out how.
- Build the data pipeline - Ingest multi-modal sensor data, synchronize streams, validate quality, and export in formats customers need. Own the full journey from sensor to deliverable dataset.
- Solve problems as they come - Debug hardware failures, adapt to new customer requirements, work around sensors that don't behave
as expected. Document what you learn so we don't hit the same wall twice.
- Shape what comes next - As we grow, this role will evolve. You'll help us figure out when to specialize, what to build vs. buy, and how to scale the operation.

You Might Be a Fit If...:
• You've built something from scratch before, a lab setup, a data collection system, a side project, a startup and you loved the ambiguity
• You default to action. When you don't know the answer, you run an experiment instead of waiting for direction
• You have hands-on experience with robotics, automation, or mechatronic systems, robot arms, drones, CNC machines, or something you built yourself. Formal years matter less than demonstrated ability to figure out unfamiliar hardware
• You're proficient in Python and comfortable building data pipelines from scratch
• You can Google your way through problems you've never seen before and you actually enjoy doing it
• You're comfortable in Linux and can pick up new tools quickly (ROS, Docker, cloud infrastructure, whatever's needed)
• You'd rather ship something imperfect and iterate than wait for perfect requirements
• You take ownership of problems end-to-end, even when they're outside your "job description"

Bonus Points:
• You've worked with VR/AR hardware, motion capture, or teleoperation systems
• You know what imitation learning is and why data quality matters for it
• You've dealt with multi-sensor synchronization or sensor fusion problems
• You've shipped something in a previous startup or early-stage environment
• You have a GitHub, blog, or portfolio that shows what you've buil

What We Offer

- Competitive salary and equity in a hyper growth startup.
- Real opportunities to grow. We’re growing insanely fast and you’ll have all the opportunities for growth that you can handle.
- Strong in person culture. We're 3-5 days a week in our newly-launched loft office in North Beach.
- Flexible PTO to recharge.
- Annual learning and development budget.
- 18 paid vacation days + federal holidays.
- Lots of opportunities for travel (all around the US, to London & Europe).
- Bi-annual off-sites and monthly socials.
- Health, dental and vision insurance.

Encord offers a unique opportunity to be part of a startup with a clear mission and vision. You will get to explore and build services enterprise AI use cases across many different industry verticals such as healthcare, surveillance, retail, agriculture, and many more.

Our work is at the cutting edge of computer vision and deep learning, which also includes working on solving unsolved problems within those fields.