🛠 Tech Stack

💼 About This Role

You'll define and lead independent research agendas on foundation model efficiency at Databricks. Your work will drive algorithmic innovations and optimize ML systems for distributed training. You'll collaborate with a team of researchers to encode scientific expertise into products that empower thousands of customers.

🎯 What You'll Do

• Define and lead independent research agendas on foundation model efficiency
• Conduct experiments to empirically validate hypotheses against state-of-the-art approaches
• Drive algorithmic innovations for large-scale neural network training or inference
• Optimize ML systems for distributed training, memory efficiency, and compute efficiency

📋 Requirements

• MS/PhD in Computer Science or related field with strong foundations in machine learning and systems
• Proven ability to write high-quality, efficient code in Python and PyTorch for research implementation
• First-author publications at top ML/systems conferences (ICLR, ICML, NeurIPS, MLSys) focused on optimization or efficiency

🎁 Benefits & Perks

• 💰 Annual performance bonus and equity
• 🏖️ Comprehensive benefits per region

📨 Hiring Process

Estimated timeline: 2-4 weeks · AI estimate

1. 1Recruiter screen· 30 min
2. 2Technical interview· 60 min
3. 3Research presentation· 60 min