Senior Staff Machine Learning Engineer, Media Intelligence

What you'll do

• Design and build scalable data-processing pipelines to transform raw media into structured, searchable intelligence.
• Architect the indexing and search infrastructure for hybrid lexical and vector retrieval across billions of assets.
• Develop retrieval interfaces and grounding contracts to enable reliable search for AI agents.
• Manage the index lifecycle, including streaming indexing, backfills, and schema versioning.
• Engineer multi-tenant isolation and data residency controls to ensure enterprise-grade security and IP protection.
• Define and enforce retrieval quality gates using offline and online evaluation metrics like recall@k and nDCG.
• Optimize the platform's performance and cost envelope, including query latency SLAs and GPU-accelerated enrichment.
• Provide technical leadership by setting standards, mentoring engineers, and driving cross-organizational design decisions.

What we're looking for

• 10+ years of experience in machine learning, data, or infrastructure engineering with deep ownership of large-scale production systems.
• MS or PhD in Computer Science, Computer Engineering, or a related field, or equivalent practical experience.
• Deep expertise in designing and operating search and retrieval infrastructure, including vector/ANN, lexical search, and hybrid retrieval.
• Strong data engineering foundations in large-scale batch and streaming pipelines using tools like Spark, Beam, Flink, or Ray.
• Experience building retrieval systems for LLMs and agentic systems, including RAG, multimodal search, and grounding.
• Proficiency in Python and a systems language like Go, Rust, or C++ (preferred).
• Hands-on familiarity with embedding models and inference paths using PyTorch.
• Proven technical leadership experience mentoring senior engineers and driving cross-organizational design decisions.