Senior Applied ML Engineer - Systems & Optimization

Fdetimes; San Francisco (CA); On-site; USD 166,000 - 210,000; Full time

Job summary

Databricks is seeking a Senior Applied ML Engineer on the Applied AI team to leverage ML, scheduling, and optimization algorithms across the infrastructure stack, from cluster management to query compilation. You will solve high-impact engineering problems to deliver optimized workloads for customers.

Responsibilities include accelerating serverless growth, building end-to-end ML4Sys solutions, and deploying state-of-the-art models that improve product performance and cost efficiency, with a

Qualifications

• Background in Computer Science and a Master's degree in Machine Learning, Data Science, or a related computational field.
• Strong background in building, training, and deploying machine learning models in production.
• Practical familiarity with cloud computing, distributed systems, and modern data processing frameworks.
• Proficiency in Python, Scala, or Java.

Skills

ML engineering

Distributed systems

Python/Scala/Java

Education

Master's degree in ML/DS or related field

Bachelor's degree in CS

Job description

Databricks is seeking a Senior Applied ML Engineer on the Applied AI team to leverage ML, scheduling, and optimization algorithms across the infrastructure stack, from cluster management to query compilation. You will solve high-impact engineering problems to deliver optimized workloads for customers.

Responsibilities include accelerating serverless growth, building end-to-end ML4Sys solutions, and deploying state-of-the-art models that improve product performance and cost efficiency, with a