Senior Applied ML Engineer - ML4Sys
$166k - $210k • Remote • San Francisco, California
Posted 26d ago
Job Location
San Francisco, California
Tech Stack
Remote Work Policy
Fully remote
Categories
Applied AI Engineer
About the job
As a Senior Applied ML Engineer on the Applied AI team, you will leverage machine learning, scheduling, and optimization algorithms to enhance the efficiency and performance of Databricks' infrastructure. Your responsibilities will encompass the full technology stack, from cluster management to query compilation, tackling complex, high-impact engineering challenges to deliver optimized and cost-effective workloads for customers. This role is crucial for accelerating serverless growth, building end-to-end ML4Sys solutions, shaping applied ML strategy, and driving the deployment of state-of-the-art models.
Responsibilities
- Drive the scaling and efficiency of Databricks serverless compute products through advanced optimization techniques.
- Design and build end-to-end ML4Sys solutions from the ground up.
- Define the roadmap for applied ML investments by collaborating with engineering and product leaders.
- Architect, train, and deploy state-of-the-art models to improve product performance and cost efficiency.
- Build robust ML pipelines, data processing layers, model serving components, and production monitoring systems.
- Research and implement novel modeling techniques for computer systems and distributed environments.
Requirements
- Master's degree in Machine Learning, Data Science, or a related computational field (AI, Bioinformatics, EE, Physics, etc.) with a background in Computer Science.
- Strong experience 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.
Benefits
- Eligibility for annual performance bonus
- Equity
- Comprehensive benefits and perks