Senior Software Engineer, ML Infrastructure

📋 Description Own fulfilment-ranking pipelines from training orchestration and quality gates through deployment Build and operate an offline-evaluation platform, combining LLM-as-judge harnesses with Develop the Roku Entertainment Assistant's LLM agent, including tool routing, retrieval, guardrails Design caching as an intentional latency and cost lever for high-volume services. Build observability for ML and LLM systems, including latency attribution, quality metrics, tracing Improve the reliability and operability of distributed systems, and lead the diagnosis of difficult 🎯 Requirements Strong production software-engineering experience, including designing, testing, operating and Meaningful ownership of ML infrastructure or production model delivery, with clear evidence of your A practical understanding of the ML lifecycle: training, evaluation, versioning, deployment, online Experience designing for latency, resilience, observability and cost in production systems. Experience with LLMs, embeddings, semantic search, retrieval or agent systems, including how you Experience with caching systems and the trade-offs involved in using caching for low-latency 🎁 Benefits Global access to mental health and financial wellness support and resources. Local benefits include healthcare (medical, dental, and vision), life, accident, disability Support for time off and evolving work and life needs.