Job Description
We're building the AI foundation for a company operating at billion-user scale. As Head of AI Engineering, you own everything that lets 200+ Data Scientists and MLEs ship models to production fast, reliably, and cost‑efficiently.
If training is slow, serving is down, GPUs are idle, or models take 6 months to ship — that's on you. If we 10x ML iteration speed and cut infra costs 50%, that's also on you.
This is a 01 build: we have the mandate, budget, and headcount. We need you to set the vision and hire the team.
What You’ll Own
1. ML Platform & MLOps – The Paved Road
- Training platform: distributed PyTorch/TF, hyperparameter tuning, experiment tracking, spot management
- Feature platform: real-time + batch feature store, online/offline consistency, lineage
- Model lifecycle: registry, CI/CD, canary deploys, rollbacks, A/B infra, shadow testing
- Monitoring: data drift, model decay, latency, cost attri...