🛠 Tech Stack

💼 About This Role

You'll lead a research team advancing large-scale machine learning efficiency at Databricks, focusing on post-training, RL, and inference optimization. You'll define the scaling research roadmap and drive breakthroughs into the Databricks AI platform.

🎯 What You'll Do

• Define research roadmap for foundation model efficiency.
• Lead algorithmic innovations in optimizers and low-precision techniques.
• Collaborate with systems teams to optimize distributed training and inference.
• Mentor researchers and engineers in scientific excellence.

📋 Requirements

• Proven ability to lead a research team in foundation model efficiency.
• Deep expertise in generative AI, LLMs, or distributed ML systems.
• Strong programming skills in Python and PyTorch.
• Demonstrated ability to translate research into scalable product capabilities.

✨ Nice to Have

• Experience at the intersection of systems and ML (distributed training frameworks, compiler optimization).
• Strong network in large-scale ML with top conference publications.
• Record of first-author publications at ICLR, ICML, NeurIPS, or MLSys.

🎁 Benefits & Perks

• 🏖️ Comprehensive benefits package including health, dental, vision.
• 💰 Equity grants and competitive compensation.
• 📈 Professional development and conference attendance support.
• 🍽️ Free meals and snacks at office locations.
• 🏋️ Wellness programs and gym reimbursements.

📨 Hiring Process

Estimated timeline: 3-5 weeks · AI estimate

1. 1Recruiter Screen· 45 min
2. 2Technical Interview· 60 min
3. 3Onsite (4-5 rounds)· 4 hours