AI / ML Engineering Lead

We’re looking for a true player-coach. We need a technical leader who can chart the long-term course but is still genuinely excited to open up an IDE, review pull requests, and write code. In this role, you’ll be the bridge between our engineering team, product managers, and clients—taking rough ideas and turning them into stable, reliable AI systems.

Here’s what you’ll be doing:

• Leading the charge:

  Guiding a cross-functional team of engineers, data, and product folks.

• Staying in the weeds:

  Making the hard architectural calls and contributing directly to the codebase.

• Talking to clients:

  Jumping on calls to figure out what clients actually need and designing the right solutions.

• Owning the lifecycle:

  Pushing projects all the way from messy, early-stage exploration to a polished production rollout.

• Raising the bar:

  Figuring out our best practices for testing, shipping, and maintaining ML systems so we aren't constantly putting out fires.

• Growing the team:

  Mentoring engineers and leveling up the technical depth of the entire organization.

• Working globally:

  Syncing up with a distributed team across a few different time zones.

What you need to bring to the table:

• Leadership background:

  You’ve successfully managed or led technical teams before.

• Bilingual fluency:

  You can confidently communicate and present in both English and Chinese.

• Client empathy:

  You know how to talk to stakeholders without drowning them in jargon, and you approach problems with a practical, service-first mindset.

• Engineering chops:

  You're a software engineer at heart. Python is a strict requirement, plus deep experience in at least one other programming language.

• Real ML experience:

  You haven't just plugged into APIs; you’ve actually built and trained models from scratch using classical machine learning techniques.

• LLM expertise:

  You know how Large Language Models actually work under the hood. You understand their limitations, their trade-offs, and the realities of keeping them running in production.

• Educational background:

  You have a strong academic foundation in a rigorous technical field.

The absolute must-haves:

• You’ve kept ML systems alive in production (handling scaling, monitoring, and reliability).
• You know your way around cloud infrastructure and data pipelines.
• You have actual experience hiring engineers and building out teams.
• You don’t panic when things are moving fast or the roadmap is a bit ambiguous.

The bottom line:

At the end of the day, we care about people who own their work, communicate plainly, and make pragmatic tech choices. You need to enjoy collaborating with everyone from hardcore engineers to non-technical clients, and be motivated by shipping things that people actually use.

The Details:

• Location:

  Flexible / Remote and Local mixed

• Type:

  Full-time