{"id":1169763,"url":"https://alion.io/job/hewlett-packard-enterprise-ai-and-hpc-systems-performance-engineer","title":"AI and HPC Systems Performance Engineer","company":{"id":5292,"name":"Hewlett Packard Enterprise","domain":"hpe.com","url":"https://alion.io/company/hewlett-packard-enterprise","size_band":"5000+","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Workday","truth_index":{"grade":"B","score":79,"open_postings":130,"ghost_share":0,"stale_share":0.831,"repost_share":0.008,"time_to_fill_p50_days":33,"computed_at":"2026-10-23T05:54:15Z"}},"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":["Bengaluru, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":33000,"max_usd":69000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":38},"experience_years_min":8,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"HPC","optional":false},{"name":"Linux","optional":false},{"name":"Bash","optional":true},{"name":"C++","optional":true},{"name":"CUDA","optional":true},{"name":"DeepSpeed","optional":true},{"name":"Docker","optional":true},{"name":"Hugging Face","optional":true},{"name":"InfiniBand","optional":true},{"name":"JAX","optional":true},{"name":"Kubernetes","optional":true},{"name":"LLM","optional":true},{"name":"Megatron-LM","optional":true},{"name":"Multimodal AI","optional":true},{"name":"NCCL","optional":true},{"name":"ONNX Runtime","optional":true},{"name":"Python","optional":true},{"name":"PyTorch","optional":true},{"name":"RAG","optional":true},{"name":"Ray","optional":true},{"name":"Redis","optional":true},{"name":"SGLang","optional":true},{"name":"TensorRT","optional":true},{"name":"TensorRT-LLM","optional":true},{"name":"Transformers","optional":true},{"name":"vLLM","optional":true}],"status":"live","first_seen_at":"2026-08-14T00:00:00Z","employer_posted_date":"2026-08-14","last_verified_at":"2026-10-23T00:33:15Z","board_verified":true,"closed_at":null,"days_open":70,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":70},"description":"AI and HPC Systems Performance EngineerThis role has been designed as 'Hybrid' with a requirement that you will work on average 2 days per week from an HPE office.Who We Are:\nHewlett Packard Enterprise is the global edge-to-cloud company advancing the way people live and work. We help companies connect, protect, analyze, and act on their data and applications wherever they live, from edge to cloud, so they can turn insights into outcomes at the speed required to thrive in today’s complex world. Our culture thrives on finding new and better ways to accelerate what’s next. We know varied backgrounds are valued and succeed here. We have the flexibility to manage our work and personal needs. We make bold moves, together, and are a force for good. If you are looking to stretch and grow your career our culture will embrace you. Open up opportunities with HPE.\nJob Description:\nHigh Performance Computing, AI and Labs is a critical element of HPE. We are focused on delivering innovative solutions that accelerate our customers’ digital transformation, enabling them to tackle their complex, and data-intensive workloads. Combining deep expertise and the development of the world’s most cutting-edge, high-performance supercomputers, is defining the next era of computing delivering valuable insight & innovation. Join us and redefine what’s next for you.\nWe are looking for an experienced AI Performance Engineer with expertise in tuning GPU server performance for a variety of Artificial Intelligence (AI) training and inference workloads running on Linux platforms. The ideal candidate will be a senior or principal-level engineer with demonstrated experience installing, configuring, characterizing, and optimizing industry-standard server infrastructure including compute, storage, networking, and accelerator technologies for AI workloads.\nThe individual in this role will investigate workload behavior by capturing and analyzing system telemetry, profiling data, traces, and performance metrics to characterize workload execution and identify opportunities for optimization through software, firmware, and hardware configuration changes. They will work closely with customers, partners, and internal engineering teams to optimize performance and scalability of AI solutions deployed on HPE platforms.\nThis role requires strong research, analytical, and problem-solving skills, along with experience building, deploying, optimizing, and maintaining containerized AI/ML environments and workloads. The engineer will collaborate with software development teams to capture workload telemetry, improve observability, and optimize AI software stacks running on HPE infrastructure.\nThey should understand the performance and capacity characteristics of modern AI training and inference workloads and be comfortable working independently to evaluate emerging technologies, author technical papers, and develop AI reference architectures.\nExperience troubleshooting complex, multi-tier software systems and distributed AI environments is highly desirable. Experience with one or more of PyTorch, JAX, Hugging Face Transformers, DeepSpeed, Megatron-LM, Ray, vLLM, SGLang, TensorRT-LLM, Dynamo, ONNX Runtime, Kubernetes, Redis, Vector Databases, Retrieval-Augmented Generation (RAG) architectures, distributed training and inference, and large-scale AI/LLM workloads is highly desired.\nThe ideal candidate will also have experience characterizing and optimizing performance across multi-GPU and distributed AI environments utilizing modern GPU interconnect, networking, and storage technologies.\nStrong written and verbal communication skills are required.\nWhat you’ll do:\nInstall, configure, and optimize complex AI infrastructure components including GPU servers, storage systems, high-speed networking, and AI software stacks.\nDevelop automation scripts, deployment frameworks, and Infrastructure-as-Code solutions to streamline AI platform provisioning and workload execution.\nPerform system-level performance characterization and optimization of AI training and inference workloads on HPE platforms utilizing GPU accelerators and distributed computing technologies.\nDesign, execute, and analyze performance benchmarks for AI/ML workloads, including large language models (LLMs), multimodal models, Retrieval-Augmented Generation (RAG) pipelines, and distributed training environments.\nCharacterize and optimize performance across multi-GPU and distributed AI environments using modern interconnect, storage, and networking technologies such as InfiniBand, Ethernet fabric, GPUDirect, and RDMA.\nCapture, analyze, and interpret system telemetry, performance metrics, logs, traces, and profiling data to identify bottlenecks and optimization opportunities.\nDevelop tools, software, and automation frameworks to improve AI workload observability, performance analysis, scalability testing, and benchmark execution.\nCollaborate with customers, partners, and internal engineering organizations to characterize, troubleshoot, and optimize AI solutions deployed on HPE infrastructure.\nWork closely with ISV, IHV, GPU vendor, and open-source ecosystem partners to evaluate, optimize, and validate AI software and hardware solutions.\nEvaluate emerging AI frameworks, models, accelerators, and infrastructure technologies; provide technical recommendations and performance guidance.\nAuthor technical reports, white papers, reference architectures, benchmark studies, and best-practice guidance for AI performance optimization and solution design.\nDocument findings, performance issues, and optimization recommendations, and communicate technical results to engineering teams, customers, and management.\nProvide technical leadership, mentoring, and guidance to junior engineers and contribute to the development of performance engineering best practices.\nCommunicate project status, technical risks, and performance findings to management and stakeholders in a timely manner.\nWhat you need to bring: \nTypically 8+ years of experience\nStrong experience with Linux system administration and command-line environments across multiple enterprise Linux distributions.\nExperience with modern AI/ML frameworks and ecosystems including PyTorch, JAX, Hugging Face Transformers, and related technologies.\nExperience with AI model training, inference, benchmarking, performance characterization, and optimization.\nExperience with data analysis, statistical methods, experiment design, and performance modeling techniques.\nExperience conducting technical research and evaluating emerging AI technologies, frameworks, and hardware platforms.\nExperience with high-performance networking technologies including InfiniBand, RDMA, RoCE, and Mellanox/NVIDIA networking solutions.\nStrong analytical, troubleshooting, and root-cause analysis skills.\nProficiency in one or more programming or scripting languages such as Python, Bash, Go, C++, or similar.\nExperience working with complex, distributed, multi-layer software systems and AI infrastructure stacks.\nExperience using performance profiling, tracing, observability, and benchmarking tools to analyze system and application performance.\nExperience with containerized and orchestrated environments including Docker, Kubernetes, and related cloud-native technologies.\nExperience analyzing and optimizing AI workloads running on GPU-accelerated systems.\nExperience with distributed training and inference frameworks and large-scale AI/LLM workloads.\nExperience with GPU accelerator technologies, memory hierarchies, and AI software stacks including CUDA, NCCL, and related ecosystem tools.\nExperience with distributed GPU environments and multi-node AI clusters.\nExperience with LLM serving frameworks such as vLLM, TensorRT-LLM, SGLang, or similar technologies.\nAptitude for self-learning; Learns new concepts quickly\nExcellent written and verbal communication; mastery in English.\nAble to work well in a team environment and perform well under pressure\nExperience with tuning system performance in a benchmarking environment\nDesired Skills and Experience\nMS/ME/MTech or PhD in Computer Science, Computer Engineering, Electrical Engineering, Data Science, Artificial Intelligence, or a related technical discipline.\n 5+ years of experience in AI/ML infrastructure, performance engineering, high-performance computing (HPC), or related technical fields.\nExperience with large-scale AI training and inference environments supporting foundation models and large language models (LLMs).\nExperience with HPE platforms, AI Factory architectures, or enterprise AI infrastructure solutions.\nExperience with parallel and distributed storage technologies, including Weka, Lustre, BeeGFS, GPFS, or similar high-performance file systems.\nExperience with AI benchmarking methodologies and industry benchmarks such as MLPerf.\nExperience developing reference architectures, technical papers, benchmark studies, or performance guidance documentation.\nExperience working directly with customers, partners, and cross-functional engineering teams in highly collaborative environments.\nExperience optimizing performance across multi-GPU and multi-node AI environments using InfiniBand, RDMA, GPUDirect, or equivalent technologies.\nAbility to work independently in globally distributed teams with minimal supervision.\nWhat We Can Offer You:\nHealth & Wellbeing\nWe strive to provide our team members and their loved ones with a comprehensive suite of benefits that supports their physical, financial and emotional wellbeing.\nPersonal & Professional Development\nWe also invest in your career because the better you are, the better we all are. We have specific programs catered to helping you reach any career goals you have - whether you want to become a knowledge expert in your field or apply your skills to another division.\nUnconditional Inclusion\nWe are unconditionally inclusive in the way we work and celebrate individual uniqueness. We know varied backgrounds are valued and succeed here. We have the flexibility to manage our work and personal needs. We make bold moves, together, and are a force for good.\nLet's Stay Connected:\nFollow @HPECareers on Instagram to see the latest on people, culture and tech at HPE.\n#india#highperformancecomputeJob:\nEngineeringJob Level:\nTCP_04HPE is an Equal Employment Opportunity/ Veterans/Disabled/LGBTemployer. We do not discriminate on the basis of race, gender, or any other protected category,and all decisions we make are made on the basis of qualifications, merit, and business need. Our goal is to be one global team that is representative of our customers, in an inclusive environment where we can continue to innovate and grow together. Please click here: Equal Employment Opportunity.\nHewlett Packard Enterprise is EEO Protected Veteran/ Individual with Disabilities.\nHPE will comply with all applicable laws related to employer use of arrest and conviction records, including laws requiring employers to consider for employment qualified applicants with criminal histories.\nRecruitment Fraud Alert\nWe have become aware of an increase in fraudulent recruitment activities in which individuals impersonate our company or authorized recruitment agencies to offer fake employment opportunities. These scams may occur through false websites, emails, social media, or chat-based applications and often aim to obtain personal information or money. Please note that Hewlett Packard Enterprise (HPE), its direct and indirect subsidiaries and affiliated companies, and its authorized recruitment agencies/vendors will never charge a candidate a registration fee, hiring fee, or any other fee in connection with its recruitment and hiring process. We also never request personal information such as back account details, Social Security numbers, or national IDs via social media or chat applications.\nAll legitimate job opportunities will come through official company channels, and candidates are responsible for verifying the credentials of any th...","description_format":"text","description_chars":12331,"description_truncated":true,"requirements":{"experience_years_min":8,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"master","optional":false},"security_clearance":false,"languages":[]},"benefits":["Professional development"],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["Cloud Platforms (IaaS & PaaS)","Enterprise Storage Systems","Network Equipment","High-Performance Computing"],"lifecycle":[{"event":"open","at":"2026-09-24T06:21:09Z"}],"visa":[],"liveness":{"score":13,"band":"cold","label":"Long shot","p_open":1,"p_active":0.457,"p_room":0.28,"age_days":70,"expected_fill_days":33,"reasons":["conf:5","stale_co","velocity","win:tail","crowd:brand"],"computed_at":"2026-10-23T05:54:15Z"},"pay":null,"html_url":"https://alion.io/job/hewlett-packard-enterprise-ai-and-hpc-systems-performance-engineer","json_url":"https://alion.io/job/hewlett-packard-enterprise-ai-and-hpc-systems-performance-engineer.json","meta":{"generated_at":"2026-10-23T15:08:29Z","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":22787,"day_limit":null,"remaining_today":null,"minute_limit":300,"resets_at":"2026-10-24T00:00:00Z"}},"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":5292},"rest":"https://alion.io/mcp/rest/get_company?id=5292"},"human":"https://alion.io/catalog?offer=company.slices&for=job%2Fhewlett-packard-enterprise-ai-and-hpc-systems-performance-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%2Fhewlett-packard-enterprise-ai-and-hpc-systems-performance-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%2Fhewlett-packard-enterprise-ai-and-hpc-systems-performance-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/hewlett-packard-enterprise-ai-and-hpc-systems-performance-engineer\", \"note\": \"what you need it for\"}"},"human":"https://alion.io/catalog?offer=company.verify&for=job%2Fhewlett-packard-enterprise-ai-and-hpc-systems-performance-engineer"}]}