Machine Learning Engineer, Local Search & Marketplace
$190,000–$300,000 year
On-siteMountain View Santa Clara County, California, United States
Job Summary
Build and improve machine learning models for search, recommendation, ranking, retrieval, matching, and personalization. Develop systems that understand user queries, behaviors, preferences, and context using embeddings, natural language processing, large language models, and modern retrieval techniques. Apply these technologies to connect consumer demand with relevant local content, businesses, or services. Build and optimize end-to-end ML pipelines, from data preparation and model training to online serving and monitoring. Partner with product, engineering, and data teams to define problems, identify opportunities, and translate business needs into scalable ML solutions. Design and analyze online and offline experiments to measure model quality and product impact. Improve key product outcomes such as relevance, engagement, conversion, retention, and marketplace efficiency. Explore new ML and LLM techniques and bring them into production where they can deliver measurable value.
Required Qualifications
- Experience building machine learning, data mining, search, recommendation, ranking, NLP, or related systems through academic projects, internships, or industry work
- Strong programming skills in Python, Java, C++, or another relevant language
- Solid understanding of machine learning fundamentals, data structures, algorithms, and statistical analysis
- Ability to work with large-scale or complex datasets and translate ambiguous problems into practical solutions
- Strong collaboration and communication skills
- Interest in building production systems that serve real users and deliver measurable product impact
Desired Qualifications
- Experience deploying and maintaining machine learning models in production
- Experience with experimentation, including A/B testing, causal analysis, or marketplace experiments
- Familiarity with deep learning frameworks and ML infrastructure, such as PyTorch, TensorFlow, Spark, Kubernetes, or feature and model-serving platforms
- Experience building taxonomies, user-interest representations, knowledge graphs, or behavioral models
- Experience applying LLMs to search, recommendation, classification, or information retrieval
- Background in local search, local services, maps, commerce, marketplaces, delivery, mobility, or location-based products
- Experience at a consumer internet, search, recommendation, advertising, e-commerce, or marketplace company
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