Meet Rad - Head of Engineering at Encord

Welcome to the first edition of ‘Meet the Encord Eng Leads’, a mini series where we sit down with the team behind the code to learn more about life (and engineering) at Encord.

In this edition, we’re chatting with Rad, one of Encord’s founding engineers and now squad lead for our physical AI tooling team. From real-time 3D visualisation to multi-sensor fusion and robotics infrastructure, Rad’s team is working on some of the most exciting engineering problems in the AI space. We dive into what it’s like to build cutting-edge tools, the problem his squad is solving and the future of Encord! 

We are also hiring for a number of engineering roles in UK & SF! You can find them here: https://encord.com/careers/ or reach out to Kerry for more info.

 So Rad, let’s kick things off! What’s your role at Encord, and what are you currently working on?

Rad: I joined Encord as the founding engineer 4 years ago, and over time I’ve worked across a wide range of projects. These days, I lead a squad focused on what we call physical AI tooling — building out the platform capabilities to support robotics, autonomous vehicles, and other embodied AI systems.

What kind of problems are you solving right now?

Rad: We’re tackling problems at the intersection of user experience, ML infrastructure, and data tooling. Think: how do you visualize millions of data points in a way that’s actually useful? How do you build labeling workflows that feel like magic but scale like enterprise software? It’s a mix of product thinking, technical architecture, and a healthy respect for browser performance limits.

That means a lot of hands-on work with 3D sensor data — think LiDAR, radar, and multi-camera setups — and fusing those inputs into coherent scene reconstructions. We’re essentially building infrastructure to enable machines to perceive and reason about the real world. It’s not just about parsing pixels anymore; it’s about helping users create high-quality datasets and training pipelines for AI systems that interact physically with their environment.

It’s exciting because most models today still operate in digital-only domains — text, audio, static images. But the physical world is where AI gets really interesting (and useful). Helping move the field from sci-fi to real-world impact — whether that’s safer self-driving cars or smarter home robotics — is incredibly rewarding engineering.

And why does working on this problem space excite you?

Rad: It’s the frontier of AI. Everyone’s focused on large language models, but what happens when those models need to drive a car or fly a drone? Suddenly, clean data, spatial awareness, and real-time feedback loops matter — a lot. That’s our domain.

It’s messy, complex, and you can’t just throw more compute at the problem. You need better tools, better data, and thoughtful engineering. That’s what we’re building.

So, what originally drew you to Encord?

Rad: A few things: the mission, the people, and the chance to work on some very non-trivial engineering problems. We’re enabling the future of AI — helping teams working on everything from autonomous vehicles to surgical robotics. And during the interviews, it was clear this wasn’t just a smart team — it was a kind one, too. High standards, low ego. That's rare.

Surgical robotics! Wow. Could you also tell us a bit about your squad?

Rad: Curious, high-trust, and delightfully nerdy. We move fast, but we’re thoughtful. Everyone’s got strong opinions, but there’s no ego — just a shared desire to build great stuff. Debugging a race condition feels like a team sport, and shipping something weirdly performant gets you Slack kudos and probably a meme. It’s a good mix of serious engineering and not taking ourselves too seriously.

Sounds pretty awesome. What advice would you give to someone thinking about joining the team?

Rad: Be curious, be proactive, and bring your whole self. If you love solving hard problems, collaborating with smart humans, and shipping things that matter — you’ll fit right in. Oh, and don’t be afraid to jump into a conversation or share an idea. Initiative is always welcomed here.

What excites you most about the future of Encord?

Rad: The size of the problem we’re solving. AI is changing fast, but data tooling hasn’t caught up — especially for teams building multimodal, physical-world systems. We’re not just filling a gap; we’re building entirely new infrastructure that will become table stakes in the next few years.

It feels like we’re still early — and that’s exciting. The things we’re building now are going to shape how future AI systems get trained. 

And lastly, one word to describe life at Encord?

Rad: Alive. In the best way. It’s fast-paced, challenging, and full of people who genuinely care. You’re never just clocking in — you’re building something that could shape the future of AI. That’s pretty cool.

You can connect with Rad here. And keep your eyes peeled for the next episode!