Forward Deployed Engineer

Overview This role sits at the intersection of ML engineering and customer partnership. You will be the person who makes it real for our lab partners, going on-site to their offices, understanding their models deeply, and doing whatever it takes to get them running at production quality on Reactor's infrastructure. This is not a support role; you will be making critical technical and product decisions and working directly with the founders, and will be one of the first people to define what forward deployment looks like at Reactor. Department: Engineering Location: San Francisco What You'll Do Travel to top world model labs, integrate their models onto Reactor's infrastructure, and own the deployment end to end Profile and optimize model performance to hit the latency and throughput targets that make real-time interactive video feel real Be the voice of the lab partner inside Reactor and make product decisions that directly shape what we build next Who You Are 3+ years in ML engineering or a technical role working directly with external teams Comfortable reading and writing Python at a production level and tracing through inference pipelines to find and fix bottlenecks Strong knowledge of PyTorch and modern ML inference optimization techniques Comfortable with ambiguity, travel, and getting on a plane to unblock a partner Nice to Have Experience with diffusion models, video generation, or world models Familiarity with real-time streaming systems CUDA kernel optimization, TensorRT, or custom inference frameworks Existing relationships in the generative video or foundation model ecosystem Benefits Competitive SF salary and meaningful early equity Visa sponsorship and relocation support Generous health, dental, and vision coverage Travel covered for on-site integrations #J-18808-Ljbffr