Databricks20 days ago

Senior Applied ML Engineer - ML4Sys

Salary not specified

MARKET

15,866 ₽median for this role

Data Scientist · 112 jobs with disclosed pay

5,000half of the offers: 12,695–20,39643,793

The employer didn't disclose pay — compare with the market yourself.

San Francisco

Responsibilities

01Use machine learning, scheduling, and optimization algorithms to maximize the efficiency and performance of our infrastructure
02Work spans the entire stack—from cluster management down to query compilation
03Solve complex, high-impact engineering problems to deliver highly optimized, cost-effective workloads for our customers
04Accelerate Serverless Growth: Drive the scaling and efficiency of Databricks serverless compute products through advanced optimization techniques
05Build Systems: Design end-to-end ML4Sys solutions from the ground up within a lean team of domain experts to support
06Shape Strategy: Define the roadmap for applied ML investments by collaborating with engineering and product leaders across Databricks
07Drive Deployment: Architect, train, and deploy state-of-the-art models that directly improve product performance and cost efficiency
08Scale Infrastructure: Build robust ML pipelines, data processing layers, model serving components, and production monitoring systems to help scale
09Innovate: Research and implement novel modeling techniques tailored specifically to computer systems and distributed environments

01Background in Computer Science and Master's degree in Machine Learning, Data Science, or a related computational field (AI, Bioinformatics, EE, Physics, etc)
02Strong background in building, training, and deploying machine learning models in production
03Practical familiarity with cloud computing, distributed systems, and modern data processing frameworks
04Proficiency in Python, Scala, or Java
05PhD in AI, Data Science, or a related technical discipline (preferred)
064+ years of machine learning engineering experience in high-velocity, high-growth environment (preferred)
07Strong understanding of computer architecture, distributed computing, cloud compute, database internals, or networking (preferred)
08Experience with operations research, forecasting, markov decision processes, or other optimization algorithms for sequential decision making (preferred)
09Proven track record of optimizing large-scale distributed systems or cloud infrastructure via data-driven approaches (preferred)