Senior AI Platform & GPU Training Manager

Databricks; California (MO); On-site; USD 229,000 - 297,000; Full time

Job summary

Databricks is seeking a Senior Engineering Manager to lead the team owning the AIR product experience and its foundational infrastructure. You will shape customer-facing capabilities while ensuring scalability, extensibility, and performance of GPU training and related areas, collaborating across platform, product, infrastructure, and research.

You will mentor an engineering team, define AIR’s roadmap, drive end-to-end delivery from ideation to launch, and build observability and reliability for

Qualifications

• 8+ years of software engineering experience with 3+ years in engineering management.
• Track record building and operating GPU training infrastructure at scale (100s/1000s GPUs).
• Deep familiarity with distributed training frameworks (PyTorch, DeepSpeed, Composer, Megatron-LM) and parallelism strategies (FSDP, tensor/pipeline parallelism).
• Experience with training resilience patterns: checkpointing, elastic training, and automated failure recovery for long-running jobs.
• Understanding of GPU performance fundamentals including NCCL, interconnect topologies, and memory optimization.
• Experience building platform products with clear SLAs where you've owned the customer experience, not just the backend.
• Strong cross-functional leadership across platform, product, and research teams, with the ability to lead through ambiguity and deliver complex projects.
• Excellent collaboration and communication skills across engineering, product, and research organizations.
• BS/MS in Computer Science, Electrical Engineering, or related technical field.

Responsibilities

• Lead, mentor, and grow a high-performing engineering team responsible for the Custom Training product and its foundational infrastructure, including distributed training orchestration, cluster lifecycle, fault tolerance, and training efficiency.
• Define and own the product and technical roadmap for AIR, balancing customer experience, functionality, and foundational investments.
• Collaborate closely with product, research, platform, infrastructure teams, and customers to drive end-to-end delivery, from ideation and prioritization to launch and operation.
• Drive architectural decisions and product design for managed GPU training at scale.
• Advocate for customer needs through direct engagement, ensuring engineering decisions translate to clear product impact.
• Build observability and reliability practices for long-running, multi-node training jobs, including checkpoint strategies, failure recovery, and operational runbooks.
• Partner with recruiting to attract, hire, and develop top-tier engineering talent.

Skills

Engineering management

Distributed training

GPU training infra

PyTorch

DeepSpeed

Megatron-LM

FSDP

Checkpointing

NCCL

Cross-functional leadership

Communication

Education

BS/MS in CS/EE

Tools

NCCL

Job description

Databricks is seeking a Senior Engineering Manager to lead the team owning the AIR product experience and its foundational infrastructure. You will shape customer-facing capabilities while ensuring scalability, extensibility, and performance of GPU training and related areas, collaborating across platform, product, infrastructure, and research.

You will mentor an engineering team, define AIR’s roadmap, drive end-to-end delivery from ideation to launch, and build observability and reliability for