Senior Applied ML Engineer - ML4Sys

Навыки

• Решения на данных
• Data Lake
• Распределённые системы
• Java
• Производство
• Machine Learning
• Оптимизация и OR

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 .

Задачи

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• As a Senior Applied ML Engineer on the Applied AI team at Databricks, you will use machine learning, scheduling, and optimization algorithms to maximize the efficiency and performance of our infrastructure
• Your work will span the entire stack—from cluster management down to query compilation
• You will solve complex, high-impact engineering problems to deliver highly optimized, cost-effective workloads for our customers
• Impact You Will Have
• Accelerate Serverless Growth: Drive the scaling and efficiency of Databricks serverless compute products through advanced optimization techniques
• Build Systems: Design end-to-end ML4Sys solutions from the ground up within a lean team of domain experts to support
• Shape Strategy: Define the roadmap for applied ML investments by collaborating with engineering and product leaders across Databricks
• Drive Deployment: Architect, train, and deploy state-of-the-art models that directly improve product performance and cost efficiency
• Scale Infrastructure: Build robust ML pipelines, data processing layers, model serving components, and production monitoring systems to help scale
• Innovate: Research and implement novel modeling techniques tailored specifically to computer systems and distributed environments

Требования

• Education: Background in Computer Science and Master's degree in Machine Learning, Data Science, or a related computational field (AI, Bioinformatics, EE, Physics, etc)
• ML Experience: Strong background in building, training, and deploying machine learning models in production
• Infrastructure Knowledge: Practical familiarity with cloud computing, distributed systems, and modern data processing frameworks
• Core Coding: Proficiency in Python, Scala, or Java
• Industry Experience: 4+ years of machine learning engineering experience in high-velocity, high-growth environment

Будет плюсом

• Advanced Education: PhD in AI, Data Science, or a related technical discipline
• Systems Domain: Strong understanding of computer architecture, distributed computing, cloud compute, database internals, or networking
• Optimization: Experience with operations research, forecasting, markov decision processes, or other optimization algorithms for sequential decision making
• Scale: Proven track record of optimizing large-scale distributed systems or cloud infrastructure via data-driven approaches

Условия

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

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