Senior Applied ML Engineer - ML4Sys
$16,000–$21,000 year
On-siteSan Francisco, California, United States
San Francisco, California, United StatesOn-siteFull Time$16,000–$21,000 yearSenior LevelMasters DegreeData ServicesLarge
Full TimeSenior LevelMasters DegreeLargeData Services
Job Summary
Maximize infrastructure efficiency and performance by applying machine learning, scheduling, and optimization algorithms across the stack from cluster management to query compilation. Architect, train, and deploy state-of-the-art models to improve product performance and cost efficiency while building robust ML pipelines and production monitoring systems. Drive the scaling of serverless compute products and define the roadmap for applied ML investments by collaborating with engineering and product leaders.
Required Qualifications
- Background in Computer Science
- Master's degree in Machine Learning, Data Science, or a related computational field (AI, Bioinformatics, EE, Physics, etc)
- 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
Desired Qualifications
- PhD in AI, Data Science, or a related technical discipline
- 4+ years of machine learning engineering experience in high-velocity, high-growth environment
- Strong understanding of computer architecture, distributed computing, cloud compute, database internals, or networking
- Experience with operations research, forecasting, markov decision processes, or other optimization algorithms for sequential decision making
- Proven track record of optimizing large-scale distributed systems or cloud infrastructure via data-driven approaches
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