AI Lead

The AI Lead at TMLC sits at the intersection of hands-on engineering and technical leadership. You'll own the end-to-end delivery of AI projects — from architecture and design through to production deployment — while mentoring and guiding a team of AI, data, and GenAI engineers to do their best work.

This is not a management role that takes you off the tools. You'll still write code, make architectural decisions, and stay accountable for what ships. But you'll also set the technical standard across your projects, work directly with clients and the founder, and build the kind of team culture where hard problems get solved well.

What you'll do

• Lead the technical delivery of AI and GenAI projects end-to-end — from scoping and architecture through to production deployment and post-launch reliability.
• Mentor and guide a team of AI, ML, data, and GenAI engineers, reviewing code, unblocking problems, and raising the engineering bar across the board.
• Make and defend key architectural decisions — model selection, system design, infrastructure trade-offs — with a clear bias toward what works in production.
• Work directly with clients and the founder to shape project scope, set expectations, and communicate progress and blockers with clarity.
• Establish engineering practices across your team: code review standards, evaluation protocols, deployment checklists, and incident response.
• Stay hands-on — you will write production code, build prototypes, and get into the details when the situation calls for it.

What we're looking for

• 6–10 years of applied AI/ML engineering experience, with at least 2 years in a technical lead or senior engineering capacity.
• Broad, deep expertise across the AI stack — you can lead a data pipeline, a computer vision system, a GenAI application, and an MLOps workflow, and know where the bodies are buried in each.
• Proven track record of shipping AI systems to production in enterprise environments, not just research or demos.
• Strong technical communication — you can write a clear architecture document, present a trade-off to a client, and give direct feedback to an engineer in the same day.
• Experience mentoring engineers and raising team capability — not just doing the work yourself, but making others better at it.
• High ownership instinct — you treat the systems you lead as yours, long after they're shipped.

Bonus points

What we offer

• Competitive compensation aligned with impact
• Work alongside Kaggle Grandmasters and top AI researchers on frontier problems
• Real ownership and surface area — outcomes, not tickets
• Hybrid flexibility and a learning-first culture via TMLC Academy