Databricks

Technology

SeniorSoftwareEngineer,AIRuntime

$210–330k ~AI est. Mountain View, California, United States
Market Sentiment
HIGH DEMAND

Neural analysis suggests this role is
optimal for Senior candidates.

The Brief

“Senior Software Engineer, AI Runtime at Databricks. Skills: AI Runtime, Distributed systems, GPU training, ML systems. Drive architecture and evolution of AIR's managed GPU. Deliver scalable, high-throughput, resilient training”

What You'll Achieve.

Make training fast; Make training reliable; Make training effortless; Keep training running for days or weeks; Keep training running across thousands of GPUs; Expand technical impact; Expand business impact

Industry & Context.

Technology
Problems you'll solve

Root cause analysis

What They're Looking For.

Must Have

5+ years of experience building and operating large-scale distributed systems, Experience in GPU training infrastructure, Experience in high-performance computing, Experience in ML systems, Experience with distributed training frameworks, Experience with parallelism strategies, Understanding of training resilience patterns, Solid grasp of GPU performance fundamentals, Experience building and operating managed, multi-tenant platform products in the cloud, Foundation in algorithms, Foundation in data structures, Foundation in system design, Proven ability to deliver technically complex, high-impact initiatives, BS in Computer Science or related field

Nice to Have

MS or PhD preferred

What You'll Do.

Drive architecture and evolution of AIR's managed GPU

Solve large-scale training problems

Orchestrate multi-node jobs

Implement distributed parallelism strategies

Route GPUs dynamically

Optimize high-throughput data loading

Implement checkpoint and restore

Improve training performance

Raise accelerator utilization

Lower cost per training run

Build resilience foundations

Build observability foundations

Detect hardware failures

Recover from hardware failures

Detect software failures

Recover from software failures

Shape developer experience

Launch production training jobs

Monitor production training jobs

Debug production training jobs

Lead end-to-end engineering efforts

Contribute to core systems

Support latest accelerators

Champion engineering excellence

Mentor other engineers

Contribute to technical direction

How You'll Work.

Team & Collaboration

Partner across product teams; Partner across research teams; Partner across platform teams; Collaborate across teams

Communication Scope

Technical discussions

Process & Methodology

Roadmap planning

Full Job Description

P-1428 At Databricks, we are passionate about enabling data teams to solve the world's toughest problems — from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world's best data and AI infrastructure platform so our customers can use deep data insights to improve their business. Training and customizing state-of-the-art AI models is one of the most demanding workloads in computing, and it sits at the heart of Databricks' Mosaic AI mission. AI Runtime (AIR) is our managed platform for large-scale GPU training and fine-tuning. It gives customers on-demand access to fleets of the latest accelerators and a serverless experience that hides the complexity of provisioning, scheduling, and orchestrating multi-node jobs, with the resilience to keep training running for days or weeks across thousands of GPUs. AIR powers the full spectrum of custom training, from fine-tuning open models to pre-training frontier-scale foundation models, for some of the most sophisticated AI teams in the world. As a Senior Software Engineer for AI Runtime, you will play a critical role in building and scaling the systems that make large-scale training fast, reliable, and effortless. You will drive the architecture and evolution of the managed GPU training stack, spanning scheduling and capacity, distributed training performance, fault tolerance, and the developer experience of launching and operating jobs at scale. Beyond hands-on contributions to core systems, you will help shape the technical direction for AIR, mentor other engineers, partner across product, research, and platform teams, and contribute to the initiatives that expand the technical and business impact of custom training at Databricks. The impact you will have: Drive the architecture and evolution of AIR's managed GPU training platform, delivering scalable, high-throughput, and resilient training across fleets that span thousands of

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