Technical Lead, Machine Learning

Research and models reliably translate into production-ready solutions with clear performance and quality targets.

ML pipelines, training loops, and inference systems are stable, efficient, and maintainable.

Production issues are detected, debugged, and resolved quickly, minimizing user impact.

Team members are supported, aligned, and able to deliver high-impact ML work with minimal friction.

Iterations on models and systems are measurable, safe, and improve user experience over time.

Python

PyTorch / JAX

GPU-based training and inference system

You have built or shipped real ML systems used by people, not just demos.

You are comfortable working with large models and understanding their failure modes.

You write strong, production-grade code and care about system correctness.

You are self-directed, pragmatic, and take full ownership of outcomes.

You communicate clearly and collaborate well in small, high-trust teams.

The best products today in the world were built by small, world class teams. We are a high talent density and hands-on team. We make decisions collectively, move at rapid speed, striking a balance between shipping high quality work and learning. Joining our team requires the ability to bring structure, exercise judgment, and execute independently. Our goal is to put in hands of our users a truly magical product

If there appears to be a fit, we'll reach to schedule 3, but no more than 4 interviews.

Applications are evaluated by our technical team members. Interviews will be conducted via virtual meetings and/or onsite.

We value transparency and efficiency, so expect a prompt decision. If you've demonstrated the exceptional skills and mindset we're looking for, we'll extend an offer to join us. This isn't just a job offer; it's an invitation to be part of a team that's bringing AI to have practical benefits to billions globally.