Inference SW Engineer

This role has been designed as ‘Hybrid’ with a requirement that you will work on average 2 days per week from an HPE office., · Design, implement, and own major components of the LLM serving deployment, including engine integration, continuous batching, KV cache management and reuse, and quantized execution

· Partner with inference engineering teams and contribute to improving time-to-first-token, inter-token latency, throughput per GPU, and P95/P99 tail latency

· Build and operate distributed execution capabilities, including disaggregated prefill/decode, tensor and pipeline parallelism, and KV cache offload across GPU memory, host memory, and RDMA-attached storage

· Evaluate emerging runtimes, quantization schemes, speculative decoding, and mixture-of-experts serving, and make well-supported recommendations on adoption

· Contribute to the orchestration layer supporting the runtime, including model admission, GPU scheduling and partitioning, cache-aware request routing, and autoscaling

· Triage and resolve customer issues end-to-end, identifying root causes and improving systems and processes to prevent recurrence

· Provide insightful code and design reviews, mentor team members, and lead by example on engineering practices within the team Knowledge and Skills Required

· Familiar with LLM inference engines such as vLLM, SGLang, TensorRT-LLM, TGI, or NVIDIA NIM, including modification of engine internals, All legitimate job opportunities will come through official company channels, and candidates are responsible for verifying the credentials of any third party claiming to represent the company. Any reliance on fraudulent communication is at the individual’s own risk, and HPE disclaims legal liability for any resulting damages. If you suspect recruitment fraud, do not share personal information or make any payments and report the incident to your local authorities immediately., Leads long-term strategy and business planning for HPE Server Services. Develops strategic roadmaps, financial and business-driver models, forecasts, KPIs, competitive analyses, and performance reviews. Partners with Product Management, Sales, Finance, and Operations, advises senior executives, and oversees strategic initiatives from planning through execution. Drives resource allocation, operational efficiency, profitability, and alignment across global teams. Top Skills: Ai ToolsExcelPower BI Hewlett Packard Enterprise

Thermal Engineer (Direct Liquid Cooling) - Houston, TX

5 Hours Ago In-Office 96K-221K Annually Mid level 96K-221K Annually Mid level Artificial Intelligence * Cloud * Information Technology * Consulting Leads mechanical and thermal design for liquid-cooled servers and rack architectures. Develops cold plates, manifolds, fluid connections, tubing, and serviceability features; performs CFD, thermal analysis, and laboratory testing. Creates qualification plans covering thermal, leak, structural, vibration, materials, corrosion, and manufacturing reliability. Drives root-cause analysis, supplier and manufacturing partner engagements, technical reviews, and design decisions. Mentors engineers while ensuring cooling solutions meet performance, reliability, acoustic, power, and customer requirements. Top Skills: 3D CadComputational Fluid Dynamics (Cfd)Coolant ManifoldsCpu/Gpu Cold PlatesCreo (Pro/Engineer)Direct Liquid CoolingQuick DisconnectsThermal Interface MaterialsThermal Modeling Hewlett Packard Enterprise

· Strong understanding of inference internals, including continuous batching, paged attention, KV cache reuse and prefix caching, chunked prefill, quantization, and speculative decoding

· Working knowledge of tensor and pipeline parallelism, NCCL collective operations, and the GPU memory hierarchy and interconnect characteristics that govern them

· Advanced proficiency in Kubernetes platform architectures, including operators, custom resources, controllers, and scheduling

· Strong programming proficiency in Go and Python, with the ability to read, debug, and profile C++/CUDA using tools such as Nsight

· Familiar with debugging/profiling multi-tier application workloads such as RAG, Agents

· Excellent analytical, debugging, and problem-solving abilities

Preferred

· Upstream contribution to vLLM, SGLang, TensorRT-LLM, llm-d, LMCache, or KServe

· Disaggregated prefill/decode serving, or KV cache offload and reuse at scale

· RDMA, GPUDirect Storage, InfiniBand, or RoCE

· MIG, fractional GPU allocation, and multi-tenant GPU isolation

· On-premises, air-gapped, or regulated enterprise software delivery Experience and Education

· Minimum of 8 years of experience in Software Engineering, including 1-2+ years working directly on LLM inference runtimes or production model serving

· Degree in Computer Science or related field

Be an Early Applicant In-Office Fort Collins, CO, USA 137K-315K Annually Senior level In-Office Fort Collins, CO, USA 137K-315K Annually Senior level Designs and owns LLM inference runtime components, including engine integration, continuous batching, KV cache management, quantized execution, distributed execution, and Kubernetes orchestration. Improves latency, throughput, GPU utilization, and autoscaling across enterprise deployments. Evaluates emerging inference technologies, resolves customer issues, contributes to architecture and code reviews, mentors engineers, and leads engineering practices. Requires expertise in LLM serving, Kubernetes, Go, Python, C++/CUDA, GPU systems, and production model serving. The summary above was generated by AI Senior Inference SW Engineer, “The expected salary/wage range for this position is provided below. Actual offer may vary from this range based upon geographic location, work experience, education/training, and/or skill level.

• United States of America: Annual Salary USD 144,000 - 273,000 in Colorado // 137,000 - 315,000 in North Carolina & Texas The listed salary range reflects base salary. Variable incentives may also be offered.”, 7 Hours Ago In-Office 121K-284K Annually Expert/Leader 121K-284K Annually Expert/Leader Artificial Intelligence * Cloud * Information Technology * Consulting Owns product category strategy, business planning, pricing, positioning, and sales execution for a significant portfolio or customer segment. Provides product expertise to sales teams, leads marketing and demand-generation priorities, manages quota responsibility, analyzes market and financial performance, and develops senior relationships with internal teams, customers, partners, and vendors. The role requires advanced IT industry knowledge, complex business planning, negotiation, communication, and cross-functional leadership skills.

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Hewlett 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., HPE’s Private Cloud AI organization is seeking a Senior Software Engineer to build and evolve the model runtime within HPE AI Essentials, the inference platform used by enterprises to operate large language models on infrastructure they own, including air-gapped and sovereign environments. The core engineering challenge in this domain is not model deployment but sustained execution efficiency: achieving low tail latency and high GPU utilization on customer-owned hardware of varying generation and configuration. In this role you will design and implement key components of that runtime - engine integration, batching, KV cache management, and distributed execution - together with the Kubernetes orchestration layer that supports it.