Senior Applied ML Engineer: Systems & Optimization

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

Job summary

Databricks in San Francisco seeks a Senior Applied ML Engineer on the Applied AI team to apply machine learning, scheduling, and optimization to maximize infrastructure efficiency. You’ll span the stack—from cluster management to query compilation—and solve high-impact engineering problems to deliver optimized workloads.

You will design end-to-end ML4Sys solutions, train and deploy state-of-the-art models, and collaborate with engineering and product leaders to shape the roadmap and drive cost

Qualifications

• MS degree in ML, Data Science, or related field.
• Production ML experience: training, deployment.
• Cloud computing, distributed systems, data processing frameworks knowledge.
• Proficiency in Python, Scala, or Java.

Responsibilities

• Use ML, scheduling, and optimization to improve infrastructure.
• Design end-to-end ML4Sys solutions across a lean team of domain experts.
• Architect, train, and deploy models to improve performance and cost efficiency.
• Build robust ML pipelines, data processing layers, and production monitoring systems.

Skills

Python

Scala

Java

Education

Master's degree in ML/Data Science or related field

PhD in AI/Data Science or related field

Job description

Databricks in San Francisco seeks a Senior Applied ML Engineer on the Applied AI team to apply machine learning, scheduling, and optimization to maximize infrastructure efficiency. You’ll span the stack—from cluster management to query compilation—and solve high-impact engineering problems to deliver optimized workloads.

You will design end-to-end ML4Sys solutions, train and deploy state-of-the-art models, and collaborate with engineering and product leaders to shape the roadmap and drive cost