{"id":2756287,"url":"https://alion.io/job/nvidia-senior-ai-performance-and-efficiency-engineer","title":"Senior AI Performance and Efficiency Engineer","company":{"id":6,"name":"NVIDIA","domain":"nvidia.com","url":"https://alion.io/company/nvidia","size_band":"5000+","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Workday","truth_index":{"grade":"B","score":82,"open_postings":592,"ghost_share":0.019,"stale_share":0.66,"repost_share":0.034,"time_to_fill_p50_days":33,"computed_at":"2026-10-17T05:46:00Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":"senior","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Santa Clara, United States","New York, United States","Seattle, United States","United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":152000,"max":241500,"currency":"USD","period":"year","gross":null,"usd_annual":241500},"salary_estimate":null,"experience_years_min":5,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AWS","optional":false},{"name":"Azure","optional":false},{"name":"CUDA","optional":false},{"name":"CUDA Toolkit","optional":false},{"name":"GCP","optional":false},{"name":"HPC","optional":false},{"name":"InfiniBand","optional":false},{"name":"LLM","optional":false},{"name":"Machine Learning","optional":false},{"name":"NCCL","optional":false},{"name":"Python","optional":false},{"name":"PyTorch","optional":false},{"name":"TensorFlow","optional":false}],"status":"live","first_seen_at":"2026-03-19T00:00:00Z","employer_posted_date":"2026-03-19","last_verified_at":"2026-10-17T09:52:59Z","board_verified":true,"closed_at":null,"days_open":212,"trust":{"level":"stale","repost_count":0,"flags":["stale"],"days_open":212},"description":"We are seeking a Senior AI/ML Performance and Efficiency Engineer, GPU Clusters at NVIDIA to join our AI Efficiency efforts. As an Engineer, you will have a pivotal role in enhancing efficiency for our researchers by implementing progressions throughout the entire stack. Your main task will revolve around collaborating closely with customers to pinpoint and address infrastructure and application deficiencies, facilitating groundbreaking AI and ML research on GPU Clusters. Together, we can craft potent, effective, and scalable solutions as we mold the future of AI/ML technology!\nWhat you will be doing:\nCollaborate closely with our AI/ML researchers to make their ML models more efficient leading to significant productivity improvements and cost savings\n\nBuild tools, frameworks, and apply ML techniques to detect & analyze efficiency bottlenecks and deliver productivity improvements for our researchers\n\nWork with researchers working on a variety of innovative ML workloads across Robotics, Autonomous vehicles, LLM’s, Videos and more\n\nCollaborate across the engineering organizations to deliver efficiency in our usage of hardware, software, and infrastructure\n\nProactively monitor fleet wide utilization patterns, analyze existing inefficiency patterns, or discover new patterns, and deliver scalable solutions to solve them\n\nKeep up to date with the most recent developments in AI/ML technologies, frameworks, and successful strategies, and advocate for their integration within the organization.\n\nWhat we need to see:\nBS or similar background in Computer Science or related area (or equivalent experience)\n\nMinimum 5+ years of experience designing and operating large scale compute infrastructure\n\nStrong understanding of modern ML techniques and tools\n\nExperience investigating, and resolving, training & inference performance end to end\n\nDebugging and optimization experience with NSight Systems and NSight Compute\n\nExperience with debugging large-scale distributed training using NCCL\n\nProficiency in programming & scripting languages such as Python, Go, Bash, as well as familiarity with cloud computing platforms (e.g., AWS, GCP, Azure) in addition to experience with parallel computing frameworks and paradigms.\n\nDedication to ongoing learning and staying updated on new technologies and innovative methods in the AI/ML infrastructure sector.\n\nExcellent communication and collaboration skills, with the ability to work effectively with teams and individuals of different backgrounds\n\nWays to stand out from the crowd:\nBackground with NVIDIA GPUs, CUDA Programming, NCCL and MLPerf benchmarking\n\nExperience with Machine Learning and Deep Learning concepts, algorithms and models\n\nFamiliarity with InfiniBand with IBOP and RDMA\n\nUnderstanding of fast, distributed storage systems like Lustre and GPFS for AI/HPC workloads\n\nFamiliarity with deep learning frameworks like PyTorch and TensorFlow\n\nNVIDIA offers competitive salaries and a comprehensive benefits package. Our engineering teams are growing rapidly due to outstanding expansion. If you're a passionate and independent engineer with a love for technology, we want to hear from you.\nYour base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 152,000 USD - 241,500 USD for Level 3, and 184,000 USD - 287,500 USD for Level 4.You will also be eligible for equity and benefits.\nApplications for this job will be accepted at least until March 23, 2026.This posting is for an existing vacancy.\nNVIDIA uses AI tools in its recruiting processes.\nNVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.","description_format":"text","description_chars":4047,"description_truncated":false,"requirements":{"experience_years_min":5,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"bachelor","optional":false},"security_clearance":false,"languages":[]},"benefits":["Equity"],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["Processors, MCUs & AI Chips","Servers & Data Center Hardware","Computer Components","AI Chips & Accelerators"],"lifecycle":[{"event":"open","at":"2026-10-17T01:56:58Z"}],"visa":[],"liveness":{"score":6,"band":"cold","label":"Long shot","p_open":1,"p_active":0.215,"p_room":0.28,"age_days":212,"expected_fill_days":33,"reasons":["conf:1","stale_co","velocity","win:tail","crowd:brand"],"computed_at":"2026-10-17T05:46:00Z"},"pay":{"stated_usd_annual":241500,"is_top_pay":true},"html_url":"https://alion.io/job/nvidia-senior-ai-performance-and-efficiency-engineer","json_url":"https://alion.io/job/nvidia-senior-ai-performance-and-efficiency-engineer.json","meta":{"generated_at":"2026-10-17T10:10:14Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers","about":"Alion is a live layer of people, companies and AI agents: who they are, whether they are real and active right now, what they do and how to work with them, readable by people and by agents and paid per call.","catalog":"https://alion.io/catalog.json","usage":{"tier":"crawler_verified","counted_by":"address","units_charged":1,"used_today":13311,"day_limit":null,"remaining_today":null,"minute_limit":300,"resets_at":"2026-10-18T00:00:00Z"}},"offers":[{"id":"company.slices","title":"One company in depth, by slice","status":"live","price":{"credits":0.02,"usd":0.002,"plus_per_slice":{"credits":0.05,"usd":0.005}},"unit":"per company, plus each slice with data","note":"the employer in depth","call":{"mcp_tool":"get_company","arguments":{"id":6},"rest":"https://alion.io/mcp/rest/get_company?id=6"},"human":"https://alion.io/catalog?offer=company.slices&for=job%2Fnvidia-senior-ai-performance-and-efficiency-engineer"},{"id":"market.stats","title":"A market slice: pay, demand and time to fill","status":"live","price":{"credits":1,"usd":0.1},"unit":"per slice","note":"pay, demand and time to fill for this role and place","call":{"mcp_tool":"market_stats"},"human":"https://alion.io/catalog?offer=market.stats&for=job%2Fnvidia-senior-ai-performance-and-efficiency-engineer"},{"id":"job.search","title":"Open jobs by role, technology, place, pay and visa","status":"live","price":{"credits":0.02,"usd":0.002},"unit":"per posting in a list","note":"similar open postings","call":{"mcp_tool":"search_jobs"},"human":"https://alion.io/catalog?offer=job.search&for=job%2Fnvidia-senior-ai-performance-and-efficiency-engineer"},{"id":"company.verify","title":"Is this company real and active right now","status":"pilot","price":null,"unit":"per company","request":{"url":"https://alion.io/catalog/request","method":"POST","body":"{\"offer\": \"company.verify\", \"for\": \"job/nvidia-senior-ai-performance-and-efficiency-engineer\", \"note\": \"what you need it for\"}"},"human":"https://alion.io/catalog?offer=company.verify&for=job%2Fnvidia-senior-ai-performance-and-efficiency-engineer"}]}