{"schemaVersion":"jobsearcher.job.v1","id":"bb8ac50f89dfe5b0c993efca","url":"https://jobsearcher.com/jobs/bb8ac50f89dfe5b0c993efca","canonicalUrl":"https://jobsearcher.com/jobs/bb8ac50f89dfe5b0c993efca","title":"Staff Machine Learning Engineer","description":"Unity is building next-generation AI-driven gaming experiences with generative world models, neural rendering, and multi-modal understanding — this hands-on technical leadership role brings cutting-edge computer vision and multi-modal models into production for billions of players.\r\n$218,400 – $327,600 / yr\r\nLocation\r\nMountain View, CA\r\nOn-site\r\nSeniority\r\nStaff\r\nCompared with 41 other Engineering roles: Common across similar roles Unique to this role\r\nWhat you'll do\r\nResponsibilitiesEstablish technical vision and roadmap for computer vision and multi-modal AI (transformers, diffusion models, vision-language models)\r\nDrive design of systems for image/video understanding, generation, segmentation, detection, and multi-modal reasoning\r\nMake architectural decisions balancing quality, latency, and cost across cloud, server, and on-device targets\r\nOwn the full pipeline from research prototypes to production: training, fine-tuning, distillation, serving\r\nApply compression, quantization, pruning, and knowledge distillation for constrained environments Unique\r\nLead and mentor ML engineers; define and track KPIs for model quality, accuracy, latency, memory, and cost\r\nWhat you'll need Experience6+ years ML engineering with significant depth in computer vision and/or multi-modal modeling\r\nProduction experience with transformer-based and diffusion vision models (ViT, CLIP, Stable Diffusion, DETR, SAM)\r\nStrong full model lifecycle knowledge: data curation, training, evaluation, serving at scale\r\nFamiliarity with efficient attention, diffusion samplers, multi-modal fusion, and vision-language alignment Unique\r\nStrong Python and PyTorch skills; proven technical leadership track record\r\nPreferred: world-model/video-generation/neural rendering pipelines (NeRF, 3DGS), on-device deployment (CoreML, TFLite, ONNX), real-time graphics or game engine background Common#J-18808-Ljbffr","company":"Workman Labs","rawCompany":"workman labs","city":"Mountain View","state":"CA","isRemote":false,"isActive":false,"createdAt":"2026-08-21T01:17:25.259Z","occupations":[{"code":"15-1221.00","title":"Computer and Information Research Scientists","slug":"computer-and-information-research-scientists"},{"code":"15-1252.00","title":"Software Developers","slug":"software-developers"},{"code":"15-2051.00","title":"Data Scientists","slug":"data-scientists"}],"industries":[{"code":"513210","title":"Software Publishers","slug":"software-publishers"},{"code":"541511","title":"Custom Computer Programming Services","slug":"custom-computer-programming-services"},{"code":"541512","title":"Computer Systems Design Services","slug":"computer-systems-design-services"}],"jobPosting":{"@context":"https://schema.org","@type":"JobPosting","title":"Staff Machine Learning Engineer","description":"Unity is building next-generation AI-driven gaming experiences with generative world models, neural rendering, and multi-modal understanding — this hands-on technical leadership role brings cutting-edge computer vision and multi-modal models into production for billions of players.\r\n$218,400 – $327,600 / yr\r\nLocation\r\nMountain View, CA\r\nOn-site\r\nSeniority\r\nStaff\r\nCompared with 41 other Engineering roles: Common across similar roles Unique to this role\r\nWhat you'll do\r\nResponsibilitiesEstablish technical vision and roadmap for computer vision and multi-modal AI (transformers, diffusion models, vision-language models)\r\nDrive design of systems for image/video understanding, generation, segmentation, detection, and multi-modal reasoning\r\nMake architectural decisions balancing quality, latency, and cost across cloud, server, and on-device targets\r\nOwn the full pipeline from research prototypes to production: training, fine-tuning, distillation, serving\r\nApply compression, quantization, pruning, and knowledge distillation for constrained environments Unique\r\nLead and mentor ML engineers; define and track KPIs for model quality, accuracy, latency, memory, and cost\r\nWhat you'll need Experience6+ years ML engineering with significant depth in computer vision and/or multi-modal modeling\r\nProduction experience with transformer-based and diffusion vision models (ViT, CLIP, Stable Diffusion, DETR, SAM)\r\nStrong full model lifecycle knowledge: data curation, training, evaluation, serving at scale\r\nFamiliarity with efficient attention, diffusion samplers, multi-modal fusion, and vision-language alignment Unique\r\nStrong Python and PyTorch skills; proven technical leadership track record\r\nPreferred: world-model/video-generation/neural rendering pipelines (NeRF, 3DGS), on-device deployment (CoreML, TFLite, ONNX), real-time graphics or game engine background Common#J-18808-Ljbffr","datePosted":"2026-08-21T01:17:25.259Z","dateModified":"2026-08-21T01:17:25.259Z","hiringOrganization":{"@type":"Organization","name":"Workman Labs","sameAs":"https://jobsearcher.com"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Mountain View","addressRegion":"CA","addressCountry":"US"}},"identifier":{"@type":"PropertyValue","name":"JobSearcher","value":"bb8ac50f89dfe5b0c993efca"},"url":"https://jobsearcher.com/jobs/bb8ac50f89dfe5b0c993efca"}}