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Machine Learning Engineer

bestenouf consulting • United States
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Own and evolve large-scale recommendation systems serving tens of millions of users. Design, build, and iterate on high-throughput recommendation systems from offline training through online A/B testing. Apply LLMs and foundation models to content discovery, personalization, and developer productivity.

Key Highlights
Own core recommendation systems serving tens of millions of users
End-to-end ownership from offline training to online A/B testing
Apply LLMs and foundation models to recommendation problems
3 to 6 years of production ML and recommendation systems experience
Must work from the Bay Area, Mountain View, California
Key Responsibilities
Design, build, and iterate on high throughput, low latency recommendation systems and power core feeds
Improve retrieval, ranking, and multi-objective optimization
Own systems from offline training through online inference, A/B experimentation, and metric analysis
Identify and resolve issues across data quality, model drift, and system performance in production
Apply LLMs and foundation models to recommendation problems
Prototype quickly, validate through experiments, and push successful ideas into production
Technical Skills Required
Python PyTorch Spark
Benefits & Perks
Health, dental, and vision care for you and your family, with 100 percent coverage for the employee
Top-tier 401(K) plan with company matching
Paid time off and paid holidays
FSA, HSA, and commuter benefits programs
Team activity budget

Job Description

About the job

MeeBoss is sharing this role on behalf of Bestenouf Consulting. This role involves taking direct ownership of a core recommendation stack, improving experimentation velocity, and driving metrics from offline modeling through online A/B results. The position focuses on evolving large-scale recommendation systems and applying AI and LLM technologies to real-world production problems to enhance content discovery, personalization, and developer productivity.

Job title

Machine Learning Engineer

Location

San Francisco, CA (On-site)

Why this role

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