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Staff Applied ML Engineer

Summary

As a Staff Applied ML Engineer on the Data Team, you will apply machine learning, scheduling and optimization algorithms to improve the efficiency and performance of our engineering systems and infrastructure. From cluster management all the way down to query compilation, our Applied AI team works on some of the hardest, most interesting problems facing the business, making Databricks infrastructure and products as performant and cost-efficient as possible.

Job Description

The impact you will have:

• Build end-to-end systems from the ground up in a small team of experienced people.
• Shape the direction of our applied ML areas of investment by engaging with engineering and product teams across the company.
• Drive the development and deployment of state-of-the-art AI models and systems that directly impact the capabilities and performance of Databricks' products, infrastructure and services.
• Architect and implement robust, scalable ML infrastructure, including data storage and processing, model training and serving components, and monitoring and reporting systems to support seamless integration of AI/ML models into production environments.
• Work on novel modeling techniques in the field of ML for Systems
• Contribute to the broader AI community by publishing research, presenting at conferences, and actively participating in open-source projects, enhancing Databricks' reputation as an industry leader.

What we look for:

• 7+ years of machine learning engineering experience in high velocity, high-growth companies
• Strong understanding of both computer systems and statistics
• Large breadth of knowledge or interest in mathematical modeling beyond ML (OR, combinatorial optimization
• Experience developing AI/ML systems at scale in production or in high-impact research environments.
• Strong track record of ML modeling that goes beyond using standard libraries.
• Strong coding and software engineering skills, and familiarity with software engineering principles around testing, code reviews and deployment.
• Experience deploying, scaling and monitoring models in production; deep understanding of the unique infrastructure challenges posed by training and serving predictions in Tier 0 environments.
• Experience applying ML to systems, or forking/contributing to open-source projects are a plus.

Comprehensive health coverage including medical, dental, and vision

• 401(k) Plan
• Equity awards
• Flexible time off
• Paid parental leave
• Family Planning
• Gym reimbursement
• Annual personal development fund
• Employee Assistance Program (EAP)

Pay Range Transparency

Databricks is committed to fair and equitable compensation practices. The pay range(s) for this role is listed below and represents base 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 utilizes 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.

Local Pay Range

$192,000—$260,000 USD