{"id":2750435,"url":"https://alion.io/job/nvidia-senior-performance-engineer-llm-inference-frameworks","title":"Senior Performance Engineer - LLM Inference Frameworks","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":80,"open_postings":778,"ghost_share":0.026,"stale_share":0.725,"repost_share":0.041,"time_to_fill_p50_days":33,"computed_at":"2026-10-20T05:45:00Z"}},"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":["Yokneam, Israel","Tel Aviv, Israel","Ra'anana, Israel","Kiryat Shmona, Israel"],"countries":["IL"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":134000,"max_usd":347000,"period":"year","method":"global_role_cell_scaled_by_country","sample_n":2216},"experience_years_min":5,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Hugging Face","optional":false},{"name":"LLM","optional":false},{"name":"Python","optional":false},{"name":"PyTorch","optional":false},{"name":"Quantization","optional":false},{"name":"SGLang","optional":false},{"name":"Speculative Decoding","optional":false},{"name":"TensorRT-LLM","optional":false},{"name":"vLLM","optional":false},{"name":"TensorRT","optional":true}],"status":"live","first_seen_at":"2026-04-20T00:00:00Z","employer_posted_date":"2026-04-20","last_verified_at":"2026-10-20T10:17:06Z","board_verified":true,"closed_at":null,"days_open":183,"trust":{"level":"stale","repost_count":0,"flags":["stale"],"days_open":183},"description":"NVIDIA is hiring exceptional software engineers to build and optimize the core inference infrastructure for large language models. Join the TensorRT-LLM team - the group defining how generative AI performs at global scale on NVIDIA GPUs. We’re looking for engineers who love squeezing every drop of throughput, memory efficiency, and scalability out of modern model runtimes. Your work will directly shape the frameworks behind state-of-the-art LLM inference used across NVIDIA and the AI community. Join us to redefine what “fast” means for LLM inference - building the frameworks that power the next generation of generative AI at scale.\nWhat you'll be doing:\nDesign, implement, and optimize high-performance inference pipelines for large language models running on GPUs\n\nProfile and tune model execution across the stack - from scheduler design to kernel fusions and everything in-between\n\nDesign and experiment with memory management strategies for improved memory bandwidth optimization and cache efficiency\n\nInnovate and Implement cutting-edge techniques such as Speculative Decoding, Context Caching, and FP8/INT4 quantization to push the boundaries of tokens-per-second-per-watt\n\nDevelop and maintain benchmarking and testing systems that quantify latency, utilization, and efficiency\n\nWhat we need to see:\nBachelor's, Master's, or higher degree in Computer Engineering, Computer Science, Applied Mathematics, or related computing-focused degree (or equivalent experience)\n\n5+ years of relevant software development experience.\n\nExcellent Python programming skills, software design, and software engineering skills\n\nExperience working with deep learning frameworks like PyTorch and HuggingFace\n\nExperience profiling and debugging performance at all levels - Python runtime, PyTorch internals, and GPU utilization metrics\n\nAwareness of the latest developments in LLM architectures and LLM inference techniques\n\nProactive and able to work without supervision\n\nExcellent written and oral communication skills in English\n\nWays to stand out from the crowd:\nContributions to inference frameworks such as TensorRT-LLM, vLLM, SGLang, or similar systems\n\nDemonstrated expertise in performance modeling, memory optimization, distributed model execution or GPU execution workflows\n\nHands-on experience with NVIDIA profiling tools (Nsight Systems, PyTorch Profiler, custom benchmarking harnesses)\n\nStrong grasp of the trade-offs shaping inference efficiency: compute vs. memory, scheduling vs. batching, latency vs. throughput\n\nWidely considered to be one of the technology world’s most desirable employers, NVIDIA offers highly competitive salaries and a comprehensive benefits package. As you plan your future, see what we can offer to you and your family www.nvidiabenefits.com.","description_format":"text","description_chars":2777,"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":[{"language":"English","level":"All levels","optional":false}]},"benefits":[],"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":"2026-10-16T23:50:30Z"}],"visa":[],"liveness":{"score":6,"band":"cold","label":"Long shot","p_open":1,"p_active":0.224,"p_room":0.28,"age_days":183,"expected_fill_days":33,"reasons":["conf:32","stale_co","velocity","win:tail","crowd:brand"],"computed_at":"2026-10-20T05:45:00Z"},"pay":null,"html_url":"https://alion.io/job/nvidia-senior-performance-engineer-llm-inference-frameworks","json_url":"https://alion.io/job/nvidia-senior-performance-engineer-llm-inference-frameworks.json","meta":{"generated_at":"2026-10-20T13:50:37Z","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":15433,"day_limit":null,"remaining_today":null,"minute_limit":300,"resets_at":"2026-10-21T00:00:00Z"}},"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-performance-engineer-llm-inference-frameworks"},{"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-performance-engineer-llm-inference-frameworks"},{"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-performance-engineer-llm-inference-frameworks"},{"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-performance-engineer-llm-inference-frameworks\", \"note\": \"what you need it for\"}"},"human":"https://alion.io/catalog?offer=company.verify&for=job%2Fnvidia-senior-performance-engineer-llm-inference-frameworks"}]}