Senior Applied ML Engineer – Cloud Infra & Optimization

Databricks; 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 apply ML, scheduling, and optimization to Databricks infrastructure. You will work across the stack—from cluster management to query compilation—and tackle high-impact engineering problems to deliver optimized, cost-efficient workloads for customers.

You will build end-to-end ML systems, deploy state-of-the-art models, and push the boundaries of distributed compute by leveraging cloud platforms, data processing

Qualifications

• Strong background in building, training, and deploying ML models in production.
• Experience with cloud computing, distributed systems, and data processing frameworks.
• Proficiency in Python, Scala, or Java.

Responsibilities

• Accelerate serverless growth through optimization techniques.
• Build end-to-end ML4Sys solutions within a lean team of domain experts.
• Define the roadmap for applied ML investments with engineering and product leaders.
• Train, deploy, and monitor state-of-the-art models that improve product performance and cost efficiency.
• Scale ML pipelines, data processing layers, model serving components, and production monitoring systems.
• Research and implement novel modeling techniques for distributed environments.

Skills

ML engineering

Production deployment

Cloud computing

Distributed systems

Python

Scala/Java

Education

Master's degree in ML/DS or related field

Tools

Python

Scala

Java

Job description

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

You will build end-to-end ML systems, deploy state-of-the-art models, and push the boundaries of distributed compute by leveraging cloud platforms, data processing