{"id":583722,"url":"https://alion.io/job/hyperbolic-inference-engineer","title":"Member of Technical Staff - Inference","company":{"id":63294,"name":"Hyperbolic","domain":"hyperbolic.ai","url":"https://alion.io/company/hyperbolic","size_band":"51-200","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Ashby","truth_index":{"grade":"A","score":88,"open_postings":12,"ghost_share":0,"stale_share":0.5,"repost_share":0,"time_to_fill_p50_days":null,"computed_at":"2026-11-01T06:10:25Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":"staff","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["San Francisco, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":206000,"max_usd":409000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":890},"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Kubernetes","optional":false},{"name":"KV Cache","optional":false},{"name":"Speculative Decoding","optional":false},{"name":"Quantization","optional":true}],"status":"live","first_seen_at":"2026-09-09T16:11:11Z","employer_posted_date":"2026-09-09","last_verified_at":"2026-11-01T17:38:29Z","board_verified":true,"closed_at":null,"days_open":53,"trust":{"level":"ok","repost_count":0,"flags":[],"days_open":52},"description":"Who We Are\nHyperbolic Labs is on a mission to democratize AI by breaking down the barriers to computing power with our Open-Access AI Cloud. By making better use of idle computing resources across the globe, we offer an innovative GPU marketplace and AI inference service that promise affordability and accessibility for all. As pioneers at the intersection of AI and open-source technology, we believe in an open future where AI innovation is limited only by imagination, not by access to resources. We're looking for forward-thinking individuals who share our passion for making AI universally accessible, secure, and affordable. Join us in building a platform that empowers innovators everywhere to turn their visionary AI projects into reality.\nAbout the Role\nWe're looking for an Inference Engineer to build inference capabilities on top of Forge, our unified control plane, so customers can consume model tokens without managing GPUs and our NeoCloud partners get a full-stack path to their own token-factory offering. You'll own how models get deployed and served across clusters distributed around the world, on heterogeneous hardware.\nDeployment comes first: serving models on Forge and our Kubernetes offering, evaluating inference frameworks, and standing up the monitoring, gateways, and endpoints that make a deployment production-ready. From there the work expands into optimization, autoscaling, KV-cache orchestration, and customer inference debugging. This is the primary seat for inference at Hyperbolic - you'll build it end to end, with real influence over where the scope lands.\nWho You Are\nStrong general inference background with a broad, high-level command of the stack rather than a narrow specialty - you can reason about the whole path from request to token\n\nDeep Kubernetes experience, including hands-on ability to operate clusters in production, not just deploy to them\n\nSolid grasp of the concepts that govern inference performance: TTFT, disaggregated inference, speculative decoding, and KV cache and its inner workings\n\nFamiliarity with modern inference frameworks and serving engines, and the judgment to evaluate and select among them for a given workload\n\nWorking knowledge of NVIDIA Dynamo and how it fits into a distributed serving architecture\n\nExperience setting up monitoring, gateways, and endpoints for production inference services\n\nProven ability to build a product end to end - you've taken something from nothing to serving real traffic\n\nStrong self-initiative and comfort operating as the primary owner of an area with minimal direction\n\nGeneralist instincts: you're willing to pick up adjacent work when it's what the product needs\n\nPreferred Qualifications\nExperience spanning both inference deployment and inference optimization\n\nHands-on model optimization work - quantization, batching strategies, kernel-level tuning, or similar\n\nUnderstanding of RDMA and high-performance networking as they apply to distributed serving\n\nExperience deploying inference across heterogeneous accelerators\n\nBackground supporting customers directly on inference debugging and performance issues\n\nExperience at a GPU cloud, inference provider, or AI infrastructure company\n\nHyperbolic is an equal opportunity employer. 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