{"id":1711545,"url":"https://alion.io/job/designworks-talent-senior-gpu-performance-kernel-engineer","title":"Senior GPU Performance / Kernel Engineer","company":{"id":5026,"name":"Designworks Talent","domain":"designworkstalent.com","url":"https://alion.io/company/designworks-talent","size_band":null,"is_staffing_agency":true,"employer_type":"agency","is_intermediary":false,"listed_via":null,"ats_vendor":"Ashby","truth_index":{"grade":"A","score":88,"open_postings":7,"ghost_share":0,"stale_share":0.286,"repost_share":0,"time_to_fill_p50_days":134,"computed_at":"2026-10-03T05:45:00Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":"senior","employment_type":"full_time","work_mode":"hybrid","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Bellevue, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":151000,"max_usd":286000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":817},"experience_years_min":null,"visa_sponsorship":true,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"CUDA","optional":false},{"name":"CUDA Toolkit","optional":false},{"name":"Fine-tuning","optional":false},{"name":"Machine Learning","optional":false},{"name":"Platform Engineering","optional":false},{"name":"ROCm","optional":false},{"name":"HPC","optional":true}],"status":"live","first_seen_at":"2026-10-02T16:51:09Z","employer_posted_date":"2026-10-02","last_verified_at":"2026-10-04T00:44:03Z","board_verified":true,"closed_at":null,"days_open":1,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":1},"description":"Senior GPU Performance / Kernel Engineer\nLocation: Hybrid | Bellevue, WA (downtown)\nmultiple roles available\nOptimize the Performance Layer Powering Next-Generation AI Infrastructure\nAbout the Opportunity\nA well-funded, rapidly growing AI infrastructure company is building a next-generation cloud platform designed to power the full lifecycle of artificial intelligence. The organization is developing a comprehensive AI infrastructure, platform, and services portfolio that supports the full spectrum of AI workloads-including large-scale compute, model training, fine-tuning, inference, and emerging agentic AI applications.\nBacked by significant long-term investment, the company combines the speed, ownership, and innovation of a startup with the stability and resources of an established parent organization. Engineering teams are intentionally lean, highly collaborative, and AI-native, leveraging modern tooling and automation to build infrastructure capable of supporting the industry's most demanding AI workloads.\nWe're seeking GPU Performance / Kernel Engineers to optimize the data plane powering large-scale AI workloads. This role focuses on improving GPU utilization, reducing latency, and maximizing throughput across training and inference environments by tuning kernels, identifying performance bottlenecks, and driving efficiency across the GPU fleet.\nThe Opportunity\nThis is a high-impact engineering role focused on extracting maximum performance from large-scale GPU infrastructure. You'll work at the intersection of GPU architecture, AI workloads, systems performance, and low-level optimization.\nAs part of a highly technical infrastructure team, you'll analyze workload behavior, optimize performance-critical code paths, and develop the techniques and tooling required to operate AI systems efficiently at scale.\nThis opportunity is ideal for engineers who enjoy deep technical challenges involving GPU computing, kernel optimization, distributed AI workloads, and hardware/software performance.\nWhat You'll Do\nProfile, analyze, and optimize GPU kernels to improve latency, throughput, and overall utilization.\n\nIdentify and eliminate data-plane bottlenecks impacting GPU performance across large-scale AI workloads.\n\nTune performance-critical workloads across training and inference environments.\n\nWork closely with AI infrastructure, machine learning, and platform engineering teams to understand workload characteristics and optimize system behavior.\n\nDevelop benchmarking methodologies and performance measurement practices across GPU infrastructure.\n\nEvaluate emerging GPU technologies, performance tools, and optimization techniques as hardware platforms evolve.\n\nContribute to engineering practices that improve GPU efficiency, scalability, and reliability across the fleet.\n\nWhat We're Looking For\nStrong experience with GPU kernel development and performance optimization using technologies such as CUDA, ROCm, or comparable GPU programming frameworks.\n\nDemonstrated experience improving GPU utilization, reducing latency, or increasing throughput for production AI workloads.\n\nStrong understanding of GPU architecture, memory hierarchy, parallel computing, and the data path from application layer to hardware execution.\n\nExperience profiling and debugging performance issues in complex AI or distributed computing environments.\n\nAbility to independently own technically complex problems and drive solutions in a fast-moving engineering environment.\n\nStrong systems programming and performance engineering mindset.\n\nPreferred Qualifications\nExperience optimizing workloads across multiple GPU platforms, including NVIDIA and AMD architectures.\n\nExperience with GPU compiler technologies, runtime optimization, or low-level systems performance.\n\nContributions to open-source GPU performance projects, compiler tooling, or AI systems optimization.\n\nBackground working with large-scale AI training, inference platforms, HPC environments, or cloud GPU infrastructure.\n\nFamiliarity with GPU profiling and optimization tools such as Nsight Systems, Nsight Compute, ROCm profiling tools, or similar technologies.\n\nCompensation\nCompetitive base pay for Bellevue market\n\nCertain roles are eligible for additional rewards, including merit increases, annual bonus, and long term incentives. These awards are allocated based on individual performance\n\nU.S. based employees have access to medical, dental, and vision insurance, a 401(k) plan and company match, employees also receive per calendar year, paid holidays.\n\nLocation\nHybrid role based in the Bellevue, WA area.\n\nApproximately three days per week in the office.\n\nCandidates elsewhere in the U.S. who are open to relocation are encouraged to apply.\n\nU.S. work authorization is required. Visa sponsorship is not currently available.\n\nWhy Join?\nOptimize the performance layer behind one of the industry's most advanced AI infrastructure platforms.\n\nWork directly on GPU efficiency, kernel optimization, and large-scale AI workload performance.\n\nSolve some of the hardest challenges in AI systems engineering-maximizing utilization, minimizing latency, and scaling compute efficiently.\n\nJoin early enough to influence architecture, tooling, and performance engineering practices.\n\nCollaborate with world-class engineers building the infrastructure powering the next generation of AI applications.\n\nEnjoy the technical ownership and impact of a startup environment backed by significant long-term investment.","description_format":"text","description_chars":5488,"description_truncated":false,"requirements":{"experience_years_min":null,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":false,"languages":[]},"benefits":["Vision insurance"],"hiring_locations":[{"name":"United States","iso":"US","kind":"country"}],"hiring_excludes":[],"relocation_offered":true,"industries":[],"lifecycle":[{"event":"open","at":"2026-10-02T17:30:33Z"}],"visa":[],"liveness":{"score":54,"band":"ok","label":"Likely open","p_open":1,"p_active":0.542,"p_room":1,"age_days":0,"expected_fill_days":134,"reasons":["conf:12","agency","velocity","win:early"],"computed_at":"2026-10-03T05:45:00Z"},"pay":null,"html_url":"https://alion.io/job/designworks-talent-senior-gpu-performance-kernel-engineer","json_url":"https://alion.io/job/designworks-talent-senior-gpu-performance-kernel-engineer.json","meta":{"generated_at":"2026-10-04T01:33:48Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers","usage":{"tier":"crawler","counted_by":"address","units_charged":1,"used_today":2034,"day_limit":5000,"remaining_today":2966,"minute_limit":60,"resets_at":"2026-10-05T00:00:00Z"}}}