Senior Staff Machine Learning Engineer, Media Intelligence

What you'll do

• Build scalable data pipelines to transform raw media and model signals into structured, searchable intelligence at enterprise scale.
• Architect hybrid lexical and vector search infrastructure for both human users and AI agents.
• Develop retrieval interfaces and grounding contracts that allow agentic workflows to reason and cite results accurately.
• Manage the index lifecycle including streaming indexing, backfills, and versioning of schemas and embedding models.
• Engineer multi-tenant systems ensuring data isolation, residency, and security for enterprise customer IP.
• Establish and monitor retrieval quality gates using offline and online evaluation metrics like recall and nDCG.
• Optimize platform performance regarding query latency, throughput, and cost efficiency across GPU and storage fleets.
• Provide technical leadership by setting standards, mentoring engineers, and defining the multi-year roadmap for search infrastructure.

What we're looking for

• 10+ years of experience in machine learning, data, or infrastructure engineering.
• Proven track record of leading systems and setting technical direction across multiple teams.
• Expertise in designing and operating large-scale search and retrieval infrastructure including vector (ANN) and lexical search.
• Strong data engineering foundations with experience in large-scale batch and streaming pipelines using Spark, Beam, Flink, or Ray.
• Experience building retrieval for LLM and agentic systems, including RAG, multimodal search, and grounding.
• Proficiency in Python and familiarity with PyTorch and embedding models.
• Experience with multi-tenant systems, data isolation, and cloud infrastructure (AWS or Azure).
• MS or PhD in Computer Science, Computer Engineering, or a related field, or equivalent practical experience.