ML Infrastructure Engineer

New

Skills

AWS Deep Learning Dual-encoder models FAISS Machine Learning Monitoring PyTorch TensorFlow Two-tower models Vector retrieval

We are seeking a Senior Machine Learning Infrastructure Engineer II specializing in Personalization. This role involves managing the end-to-end ML lifecycle for recommendation systems, including generation, ranking, serving, and online evaluation.

Key Responsibilities
  • Design, train, and ship two-tower/dual-encoder models and embedding pipelines.
  • Build production ML pipelines for data preparation, training, evaluation, deployment, and monitoring.
  • Implement low-latency model serving for high-QPS recommendation traffic.
  • Collaborate with data scientists and product engineers across teams.
Required Skills & Qualifications
  • 8+ years of relevant professional experience in ML infrastructure.
  • Experience designing, training, and deploying production recommender systems.
  • Proficiency in deep learning frameworks such as PyTorch and/or TensorFlow (5+ years).
  • Experience with vector retrieval/ANN at scale (FAISS, ScaNN, OpenSearch k-NN, Pinecone, Weaviate).
  • Familiarity with AWS or similar cloud infrastructure (5+ years).
  • Ability to work in a hybrid schedule, with in-office presence three days a week in San Mateo, CA.

No forms. Your profile is generated instantly.

Job Type: Remote

Salary: Not Disclosed

Experience: Entry

Duration: Months

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