Senior Engineering Manager, AI Runtime

Benefits

Parental leave

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Non-birth-parent leave

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Family-building benefits

• Fertility benefits: Not verified
• Adoption assistance: Not verified
• Surrogacy assistance: Not verified

Mental health support

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Relocation assistance

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Childcare support

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Learning budget

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Verification

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Salary

$229K-$314K From the posting source

401(k) match

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Market context

U.S. role benchmark (BLS OEWS)

$116,543 U.S. median for this role

Projected growth (BLS Employment Projections)

+9.8% - Much faster than average

133% above the BLS role benchmark for software engineering aggregate.

Matched to SOC 15-1252 - Software Engineering aggregate by role bucket.

Source: U.S. Bureau of Labor Statistics, OEWS, May 2024 and Employment Projections, 2024-2034.

Role

Role function

Engineering From the posting source

Seniority

Senior From the posting source

Schedule

Shift type

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Weekend work

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Company

Equity

Offered From the posting source

Application

Cover letter

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Assessment

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Deadline

Not stated

Where they hire

State eligibility is not yet verified.

About this role

Senior Engineering Manager, AI Runtime Mountain View, California; San Francisco, California 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. Databricks' AI Runtime (AIR) product provides enterprises with an API for training and fine-tuning deep learning and LLM models with on-demand GPUs. Whether it's a transformer model for drug discovery or a fine-tuned foundation model, customers use this team's training infrastructure to build state-of-the-art frontier models. As a Senior Engineering Manager, you will lead the team owning both the product experience and the foundational infrastructure of AIR. You'll shape customer-facing capabilities while designing for scalability, extensibility, and performance of GPU training and adjacent areas, collaborating closely across the platform, product, infrastructure, and research organizations. The impact you will have: - 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

Read the full description at databricks.com. FewerJobs shows a preview and links to the original posting.