Staff Backend Software Engineer- (AI Platform)

Навыки

• Коммуникация
• Data Lake
• Распределённые системы
• Лидерство
• Machine Learning
• Мониторинг и observability
• Роадмап

О компании и продукте

• 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 .
• 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’ Model Serving product provides enterprises with a unified, scalable, and governed platform to deploy and manage AI/ML models — from traditional ML to fine-tuned and proprietary large language models. It offers real-time, low-latency inference, governance, monitoring, and lineage. As AI adoption accelerates, Model Serving is a core pillar of the Databricks platform, enabling customers to operationalize models at scale with strong SLAs and cost efficiency.

Задачи

• Design and implement core systems and APIs that power Databricks Model Serving, ensuring scalability, reliability, and operational excellence
• Partner with product and engineering leadership to define the technical roadmap and long-term architecture for serving workloads
• Drive architectural decisions and trade-offs to optimize performance, throughput, autoscaling, and operational efficiency for CPU and GPU serving workloads
• Contribute directly to key components across the serving infrastructure — from model container builds and deployment workflows to runtime systems like routing, caching, observability, and intelligent autoscaling — ensuring smooth and efficient operations at scale
• Collaborate cross-functionally with product, platform, and research teams to translate customer needs into reliable and performant systems
• Lead technical initiatives that improve latency, availability, and cost-effectiveness across both customer-facing and foundational serving layers
• Establish best practices for code quality, testing, and operational readiness, and mentor other engineers through design reviews and technical guidance
• Represent the team in cross-organizational technical discussions and influence Databricks’ broader AI platform strategy

Требования

• 10+ years of experience building and operating large-scale distributed systems
• Deep expertise in model serving, inference systems, and related infrastructure (e.g., routing, scheduling, autoscaling, and observability)
• Strong foundation in algorithms, data structures, and system design as applied to large-scale, low-latency serving systems
• Proven ability to deliver technically complex, high-impact initiatives that create measurable customer or business value
• Experience leading architecture for large-scale, performance-sensitive CPU/GPU inference systems
• Strong communication skills and ability to collaborate across teams in fast-moving environments
• Strategic and product-oriented mindset with the ability to align technical execution with long-term vision
• Passion for mentoring, growing engineers, and fostering technical excellence

Условия

• At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees

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