Sr. Manager, Applied ML For Systems
San Francisco, CaliforniaFull-TimeManagerAI / Data Science
Intro
- 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.
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.
Pay Range Transparency
- Databricks is committed to fair and equitable compensation practices. The pay range(s) for this role is listed below and represents the expected salary range for non-commissionable roles or on-target earnings for commissionable roles. Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to job-related skills, depth of experience, relevant certifications and training, and specific work location. Based on the factors above, Databricks anticipates utilizing the full width of the range. The total compensation package for this position may also include eligibility for annual performance bonus, equity, and the benefits listed above. For more information regarding which range your location is in visit our page here.
Our Commitment to Diversity and Inclusion
- At Databricks, we are committed to fostering a diverse and inclusive culture where everyone can excel. We take great care to ensure that our hiring practices are inclusive and meet equal employment opportunity standards. Individuals looking for employment at Databricks are considered without regard to age, color, disability, ethnicity, family or marital status, gender identity or expression, language, national origin, physical and mental ability, political affiliation, race, religion, sexual orientation, socio-economic status, veteran status, and other protected characteristics.
