Это топовая возможность создавать инфраструктуру для базовых моделей в компании-лидере рынка. Роль четко определена, стек максимально современный, а влияние на продукт будет огромным.
Staff Software Engineer (AI Runtime): Building and scaling the managed GPU training platform for large-scale AI models with an accent on distributed training performance and fault tolerance. Focus on designing multi-node orchestration, optimizing GPU efficiency, and developing resilience foundations for frontier-scale foundation models.
Location: Mountain View, California or San Francisco, California
Salary: $190,000 — $265,000 USD
Company
Databricks is a data and AI company providing a Data Intelligence Platform that unifies data, analytics, and AI for over 10,000 organizations worldwide.
What you will do
Drive the architecture and evolution of the AI Runtime (AIR) managed GPU training platform for scalable, high-throughput training.
Solve complex problems in multi-node orchestration, distributed parallelism strategies, and GPU scheduling.
Optimize GPU efficiency and training performance to raise utilization and lower cost per training run.
Build resilience and observability foundations to detect and recover from hardware and software failures.
Partner with product and research teams to shape APIs, CLI, and the developer experience for production training jobs.
Mentor senior engineers and champion engineering excellence to shape the long-term technical direction of AI training infrastructure.
Requirements
10+ years of experience building and operating large-scale distributed systems, GPU training infrastructure, or ML systems.
Hands-on experience with distributed training frameworks such as PyTorch, FSDP, DeepSpeed, or Megatron.
Deep understanding of parallelism strategies (data, tensor, pipeline, and sequence parallelism).
Strong grasp of GPU performance fundamentals, including NVLink, InfiniBand, and collective communication.
Experience building managed, multi-tenant cloud platform products with clear SLAs and SLOs.
BS in Computer Science or a related field (MS or PhD preferred).
Culture & Benefits
Comprehensive benefits and perks tailored to the employee's region.
Opportunity to work on the most demanding workloads in computing, including frontier-scale foundation models.
Collaborative environment partnering across product, research, and platform teams.
Commitment to diversity, inclusion, and equal employment opportunity standards.
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