Sr. Manager, Applied ML For Systems

RDQ127R57

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. Founded by engineers — and customer obsessed — we leap at every opportunity to tackle technical challenges, from designing next-gen UI/UX for interfacing with data to scaling our services and infrastructure across millions of virtual machines. And we're only getting started.

As a Senior Manager for Applied ML For Systems at Databricks, you will lead a team of machine learning engineers in applying ML and optimization algorithms to improve the efficiency and performance of Databrick’s infrastructure. From cluster management to job scheduling, query compilation and GPU resource optimization for large language models and other deep learning workloads your team will tackle some of the hardest and most impactful problems in the company, making Databricks infrastructure and products as performant and cost-efficient as possible. This is a high-visibility, high-impact role where you will shape technical direction, grow talent, and drive initiatives that help our customers run the most optimized workloads at scale.

The impact you will have

• Set vision and strategy for our ML-for-Systems initiatives, aligning investments with product and infrastructure priorities.
  
• Build and lead a high-performing team of applied ML engineers, providing technical guidance, mentorship, and career development.
  
• Partner with engineering and product leaders across the company to identify high-leverage opportunities for AI and optimization in infrastructure.
  
• Oversee the development and deployment of state-of-the-art AI models and optimization systems that directly improve Databricks' products, infrastructure, and services.
  
• Guide the design of robust, scalable ML solutions, ensuring best practices in data processing, model training, serving, monitoring, and reliability for Tier 0 production environments.
  
• Foster a culture of technical excellence, truth-seeking, and customer obsession.
  
• Represent Databricks in the broader AI community through publications, conference talks, and open-source contributions.
  
• Direct impact to company profitability and bottom line by driving impact worth several millions of dollars of savings.
  

What we look for

• Proven leadership experience managing applied AI or ML engineering teams in high-velocity, high-growth environments.
  
• Strong technical foundation in computer systems, statistics, and applied machine learning, with the ability to guide deep technical discussions.
  
• Breadth of knowledge or interest in mathematical modeling beyond ML (e.g., operations research, combinatorial optimization).
  
• Experience delivering ML systems at scale in production, including the infrastructure and organizational processes needed to support them.
  
• Interest/experience in compute systems such as kubernetes and spark.
  
• Track record of driving end-to-end ML projects — from identifying opportunities to delivering measurable business impact.
  
• Strong people leadership skills: hiring, coaching, and developing engineering talent.
  
• Effective cross-functional collaboration skills, with the ability to influence without direct authority.