Senior Engineering Manager, AI Runtime

📋 Description

• Lead and grow a high-performing engineering team for Custom Training infra.
• Define and own the AIR product and technical roadmap.
• Collaborate with product, research, platform, infra, and customers to deliver end-to-end.
• Drive architecture for managed GPU training at scale.
• Advocate for customer needs and translate them into product impact.
• Build observability and reliability practices for long-running multi-node jobs.

🎯 Requirements

• 8+ years software engineering with 3+ years in management.
• Track record building and operating GPU training infrastructure at scale.
• Deep familiarity with distributed training (PyTorch, DeepSpeed) and FSDP.
• Experience with checkpointing, elastic training, and automated failure recovery.
• GPU performance fundamentals: NCCL, interconnects, memory optimization.
• BS/MS in Computer Science, Electrical Engineering, or related field.

🎁 Benefits

• Pay range transparency; regional benefits information available.
• Diversity and inclusion commitment across Databricks.
• Compliance and export controls information.
• Regional benefits vary; details at the benefits page.
• Databricks offices worldwide; collaborative, innovative culture.