About Rivian Rivian is on a mission to keep the world adventurous forever. This goes for the emissions-free Electric Adventure Vehicles we build, and the curious, courageous souls we seek to attract. As a company, we constantly challenge what’s possible, never simply accepting what has always been done. We reframe old problems, seek new solutions and operate comfortably in areas that are unknown. Our backgrounds are diverse, but our team shares a love of the outdoors and a desire to protect it for future generations. Role Summary This positions requires 5 days in office a week at our Normal, IL facility. Relocation is a requirement. The role will focus on enhancing the execution efficiency of AI pipelines for employee-used AI applications. This role involves optimizing system performance across Rivian AI and AI runtimes through advanced profiling, algorithmic improvements, pipeline optimization, and hardware-software co-optimization. Responsibilities Model & pipeline design – Fine-tune and evaluate GPT-style models on Rivian’s secure GPU clusters; implement RAG, function-calling and tool-use chains for engineering math libraries (NumPy, OpenFOAM, ANSYS APIs). Systems engineering – Architect micro-services in Python/Go, expose gRPC/REST endpoints, and author Terraform modules to spin up reproducible environments. Algorithmic accuracy & safety – Develop automatic unit-tests and guardrails for dimensional-analysis sanity, physical-law consistency and PII compliance Cross-functional collaboration – Pair with design, quality, and factory-automation teams to harvest domain data, craft prompts and validate results. Observability & performance – Instrument Prometheus/Grafana dashboards, load-test with Locust, and implement vector-DB sharding strategies to keep P99 latency