Meet Jen - ML Solutions Engineer at Encord

Another day, another episode of "Behind the Enc-urtain", where we go behind the scenes with the Encord team and learn more about their life and work! Today we sit down with Jen Ding, ML Solutions Engineer here at Encord.

Our Solutions team plays a huge role in our commercial and technical progress as a company — they uncover new interesting use cases for us to support, build a strong feedback loop between our technical and commercial teams, and help empower leading AI teams across our customer base as they build cutting-edge AI applications in their F500 organizations, AI research labs and fast growing AI scale-ups.

PS. We are hiring! We are looking for Solutions Engineers to join our London and San Francisco teams - you can find more about the London SE role here and SF SE role here.

Let's start with a quick introduction — can you share a bit about your background and how you found your way to Encord?

I come to Encord from a research institute, where I was part of a team building real-world applications of AI research. I focused on topics like open source and participatory practices for AI, stewarding a UK Choral AI dataset and co-founding a public data festival called London Data Week with the Mayor of London. Before that, I was part of a couple of applied ML startups as a Data Scientist and Solutions Engineer. Joining Encord’s Solutions team is a nice return to the startup world!

How is Solutions Engineering at Encord different from Solutions Engineering in other environments? 

It’s a great moment to be an ML Solutions Engineer. In my first Solutions role years ago, Computer Vision was still an emerging research topic. My work focused more on demonstrating the potential of CV to customers by building custom models on their data to prove that it was a technology worth investing in. Now that more organisations are actively adopting and building products with AI, the work at a startup like Encord can focus more on enabling the frontier of AI applications. It’s been exciting to learn about the different AI dreams of our customers from radiology and robotics to vertical farming and video generation, and to create custom solutions with Encord’s suite of data products to help make these dreams come true. 

What is one exciting customer project you've worked on this month?

The first few that come to mind are engagements with robotics companies that are building robots to perform tasks like tidying a room, cleaning windows, or delivering drinks. It’s been exciting to learn more about this dynamic problem space, and create demos to showcase how Encord can help improve and scale key datasets for this field.

I’ve worked with colleagues from Encord’s Solutions and ML teams to build data agents that support expanding the linguistic breadth of Vision Language Action (VLA) datasets for robot tasks. I didn’t realise how challenging this problem space is, and the importance of collecting a semantically diverse set of instructions to capture the many ways different people may describe the same task. The Exact Instructions Challenge video captures how hard this problem can be for humans — let alone robots, which have a much more limited model of the world. I’m excited to see where our work in this space goes.

What’s a misconception one might have about our product space from the ‘outside’?

Data and data annotation may not be the “sexiest” of topics in the AI space. This can lead to the misconception that data work is not as important or requires less attention than training models or obtaining more compute. In fact, data quality remains one of the most important factors in model performance and efficient use of compute and is often the biggest competitive advantage for organizations adopting and applying AI within their domains.

I’ve actually been working on a side initiative in this area — a video series called “AI Data Chats”. The plan would be to invite AI researchers and practitioners to get their “AI Data Hot Take” (paired with a drink of their choice!), to create more airtime for these key data topics that are currently underrepresented in the news and research.

Now onto a rapid fire round...

What 3 words would you use to describe the Encord culture?

Dynamic, Dedicated and Customer-driven.

Which fictional character would make the best Encord hire and why? 

Naomi Nagata from The Expanse would be an amazing member of the Solutions team! Ready for any challenge — engineering, negotiation, extraterrestrial life form — that comes her way and ready to implement a creative solution in T-10 seconds. Every second counts on the Rocinante (and a customer demo!)

If you could time-travel to 2030 – what’s one thing you hope hasn’t changed about working at Encord?

The Nugget Challenge! (iykyk)

You can find Jen on Linkedin here and subscribe to AI Data Chats (which just launched this April!) here.

See you at the next episode of “Behind the Enc-urtain” 👋