Senior Software Engineer, AI Runtime

Fdetimes; Mountain View (CA); On-site; USD 160,000 - 225,000; Full time

Job summary

Databricks is seeking a Senior Software Engineer to build core parts of AI Runtime and scale its AI training infrastructure. You will own features end-to-end, improving reliability, observability, and developer experience for large-scale training jobs.

You will prepare the platform for new GPU generations, tackle complex multi-node training challenges, and work with researchers, product teams, and customers to drive impactful improvements across architectures and accelerators.

Qualifications

• 5+ years in large-scale distributed systems.
• Experience training large models with FSDP, DeepSpeed or Megatron.
• Familiarity with parallelism strategies and GPU performance.
• Knowledge of training resilience patterns: checkpointing, failure detection, automatic recovery.
• Background building and running multi-tenant cloud platforms as products.
• track record owning complex features end-to-end with customer impact.
• Ability to explain technical designs in writing and in person.

Responsibilities

• Build core parts of AI Runtime and contribute to Databricks' technical direction in AI training infrastructure.
• Develop reliability and observability features for a growing fleet.
• Improve AI Runtime's developer experience for large training jobs.
• Prepare AI Runtime for new GPU generations and workload types.
• Tackle multi-node training challenges from orchestration to data loading and checkpointing.
• Increase training speed and cost-efficiency across architectures and accelerators.
• Collaborate with research, product, and customers, owning features from design to production.
• Promote engineering excellence and mentor peers.

Skills

Large-scale distributed systems

GPU training

FSDP/DeepSpeed/Megatron

Parallelism strategies

GPU performance and kernels

Training resilience & checkpointing

Multi-tenant cloud platforms

End-to-end ownership

Written and verbal communication

Education

BS in Computer Science or related field (MS/PhD preferred)

Job description

At Databricks, we run the world's largest AI platform. We believe the next breakthroughs will come from models trained on domain-specific enterprise data, not from bigger general-purpose models alone.

That's why we built AI Runtime, a serverless product that makes GPU training of any size feel simple, so companies can train their own models the way frontier labs do. Customers across industries train on it, right next to the enterprise data already in Databricks. Among them are Rivian in automotive, Robinhood in fintech, and Merck, which builds foundation models for drug discovery. Our own AI researchers use it to post-train models with hundreds of billions to nearly a trillion parameters.

It takes a lot of engineering to make that work, and we've written about it on our blog: how we keep GPUs reliable, make training fault-tolerant, and speed up fine-tuning with fused kernels and smart sequence packing. AI agents now launch experiments too, and on our research team they've already increased training jobs 8x.

As a Senior Software Engineer, you'll work on the systems behind all of this, solving hard technical problems and helping shape how AI Runtime evolves.

The impact you will have

• Build core parts of AI Runtime and contribute to Databricks' technical direction in AI training infrastructure.
• Develop reliability and observability features for a fleet that keeps growing in scale and complexity.
• Improve AI Runtime's developer experience for people and agents, so even the largest training jobs feel as simple as a first experiment.
• Help prepare AI Runtime for new GPU generations and workload types.
• Take on hard multi-node training problems, from orchestration and GPU scheduling to data loading and checkpointing.
• Make training faster and cheaper by raising efficiency across model architectures and GPU accelerators.
• Work with research, product, and customers on what we build next and own features from design through production.
• Champion engineering excellence, raise the bar, and help the engineers around you grow.

What we look for

• 5+ years in large-scale distributed systems, with experience in GPU training, high-performance computing, or ML systems.
• Experience training large models with FSDP, DeepSpeed, or Megatron, and familiarity with parallelism strategies.
• Working knowledge of GPU performance, including accelerator architecture, high-speed interconnects, and kernels.
• Strong understanding of training resilience patterns, such as checkpointing, failure detection, and automatic recovery.
• A background in building and running multi-tenant cloud platforms as products.
• A track record of owning complex features end to end and seeing them through to customer impact.
• The clarity to explain technical designs in writing and in person, and a reputation as a teammate others learn from.
• BS in Computer Science or a related field (MS or PhD preferred).

Pay Range Transparency

Databricks is committed to fair and equitable compensation practices. The pay range(s) for this role is listed below and represents the expected salary range for non-commissionable roles or on-target earnings for commissionable roles. Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to job-related skills, depth of experience, relevant certifications and training, and specific work location. Based on the factors above, Databricks anticipates utilizing the full width of the range. The total compensation package for this position may also include eligibility for annual performance bonus, equity, and the benefits listed above. For more information regarding which range your location is in visit our page here.

Local Pay Range

$160,000—$225,000 USD

About Databricks

Databricks is the Data and AI company. More than 20,000 organizations worldwide — including adidas, AT&T, Bayer, Block, Mastercard, Rivian, Unilever, and 70% of the Fortune 500 — rely on the Databricks Data + AI Platform to build and scale data and AI apps, analytics and agents. Headquartered in San Francisco with 30+ offices around the globe, Databricks offers a unified platform that includes Genie, Lakebase, Agent Bricks, Lakeflow, Lakehouse, and Unity Catalog. To learn more, follow Databricks on LinkedIn, X, YouTube, and Instagram.

Benefits

At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees. For specific details on the benefits offered in your region click here.

Our Commitment to Diversity and Inclusion

At Databricks, we are committed to fostering a diverse and inclusive culture where everyone can excel. We take great care to ensure that our hiring practices are inclusive and meet equal employment opportunity standards. Individuals looking for employment at Databricks are considered without regard to age, color, disability, ethnicity, family or marital status, gender identity or expression, language, national origin, physical and mental ability, political affiliation, race, religion, sexual orientation, socio‑economic status, veteran status, and other protected characteristics.

Compliance

If access to export‑controlled technology or source code is required for performance of job duties, it is within Employer's discretion whether to apply for a U.S. government license for such positions, and Employer may decline to proceed with an applicant on this basis alone.