{"schemaVersion":"jobsearcher.job.v1","id":"cb816d382fd939fe00ef71e1","url":"https://jobsearcher.com/jobs/cb816d382fd939fe00ef71e1","canonicalUrl":"https://jobsearcher.com/jobs/cb816d382fd939fe00ef71e1","title":"Inference Engineer","description":"Collision AI is building frontier cybersecurity models to help defend our customers. As an Inference Engineer, you’ll build and own the inference servers that run our models, both on our infrastructure and in customer on-prem environments.\r\nYou’ll work across model runtimes and the serving layer: request scheduling, batching, caching, GPU memory management, and multi-GPU execution. You’ll profile real workloads, identify bottlenecks, and improve latency, throughput, and hardware utilization while preserving model quality. You’ll work closely with the research team to bring new models into production and support the multi-step workloads our security agents depend on.\r\nCustomer deployments are a core part of the role. You’ll make the serving stack straightforward to install, observe, update, and recover on customer-owned hardware, including environments with limited network access. You’ll build reproducible deployment tooling, sensible defaults, and reliable upgrade and rollback paths, so the same system can run well in our own fleet and inside a customer’s network.\r\nRequired qualificationsExperience building model-serving infrastructure or other performance-sensitive distributed systems.\r\nStrong software engineering skills in Python, with experience in C++, Rust, or a comparable systems language.\r\nAn understanding of LLM inference, including batching, KV-cache management, and GPU compute and memory bottlenecks.\r\nExperience profiling systems, designing reproducible benchmarks, and shipping measurable improvements to performance or reliability.\r\nWork on inference runtimes such as vLLM, SGLang, or TensorRT-LLM, including extensions or open-source contributions.\r\nExperience with CUDA or Triton, quantization, speculative decoding, or multi-GPU inference.#J-18808-Ljbffr","company":"Collision","rawCompany":"collision","city":"Millbrae","state":"CA","isRemote":false,"isActive":false,"createdAt":"2026-11-04T02:30:22.287Z","occupations":[{"code":"15-1299.08","title":"Computer Systems Engineers/Architects","slug":"computer-systems-engineers-architects"},{"code":"15-1252.00","title":"Software Developers","slug":"software-developers"},{"code":"15-1221.00","title":"Computer and Information Research Scientists","slug":"computer-and-information-research-scientists"}],"industries":[{"code":"541512","title":"Computer Systems Design Services","slug":"computer-systems-design-services"},{"code":"541511","title":"Custom Computer Programming Services","slug":"custom-computer-programming-services"},{"code":"513210","title":"Software Publishers","slug":"software-publishers"}],"jobPosting":{"@context":"https://schema.org","@type":"JobPosting","title":"Inference Engineer","description":"Collision AI is building frontier cybersecurity models to help defend our customers. As an Inference Engineer, you’ll build and own the inference servers that run our models, both on our infrastructure and in customer on-prem environments.\r\nYou’ll work across model runtimes and the serving layer: request scheduling, batching, caching, GPU memory management, and multi-GPU execution. You’ll profile real workloads, identify bottlenecks, and improve latency, throughput, and hardware utilization while preserving model quality. You’ll work closely with the research team to bring new models into production and support the multi-step workloads our security agents depend on.\r\nCustomer deployments are a core part of the role. You’ll make the serving stack straightforward to install, observe, update, and recover on customer-owned hardware, including environments with limited network access. You’ll build reproducible deployment tooling, sensible defaults, and reliable upgrade and rollback paths, so the same system can run well in our own fleet and inside a customer’s network.\r\nRequired qualificationsExperience building model-serving infrastructure or other performance-sensitive distributed systems.\r\nStrong software engineering skills in Python, with experience in C++, Rust, or a comparable systems language.\r\nAn understanding of LLM inference, including batching, KV-cache management, and GPU compute and memory bottlenecks.\r\nExperience profiling systems, designing reproducible benchmarks, and shipping measurable improvements to performance or reliability.\r\nWork on inference runtimes such as vLLM, SGLang, or TensorRT-LLM, including extensions or open-source contributions.\r\nExperience with CUDA or Triton, quantization, speculative decoding, or multi-GPU inference.#J-18808-Ljbffr","datePosted":"2026-11-04T02:30:22.287Z","dateModified":"2026-11-04T02:30:22.287Z","hiringOrganization":{"@type":"Organization","name":"Collision","sameAs":"https://jobsearcher.com"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Millbrae","addressRegion":"CA","addressCountry":"US"}},"identifier":{"@type":"PropertyValue","name":"JobSearcher","value":"cb816d382fd939fe00ef71e1"},"url":"https://jobsearcher.com/jobs/cb816d382fd939fe00ef71e1"}}