{"id":4203473,"url":"https://alion.io/job/netlist-ai-inference-systems-software-architect","title":"AI Inference / Systems Software Architect","company":{"id":691714,"name":"Netlist","domain":"netlist.com","url":"https://alion.io/company/netlist","size_band":"51-200","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Breezy","truth_index":null},"role":"Backend","role_family":"Backend","seniority":"staff","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Irvine, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":275000,"max":null,"currency":"USD","period":"year","gross":null,"usd_annual":275000},"salary_estimate":null,"experience_years_min":10,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"CUDA","optional":false},{"name":"Edge AI","optional":false},{"name":"KV Cache","optional":false},{"name":"Mixture of Experts","optional":false},{"name":"Multimodal AI","optional":false},{"name":"PyTorch","optional":false},{"name":"Quantization","optional":false},{"name":"RAG","optional":false},{"name":"ROCm","optional":false},{"name":"Speculative Decoding","optional":false},{"name":"TPOT","optional":false},{"name":"Triton","optional":false},{"name":"vLLM","optional":false},{"name":"C++","optional":true},{"name":"LLM","optional":true},{"name":"LLVM","optional":true},{"name":"MLIR","optional":true},{"name":"Python","optional":true},{"name":"TensorRT","optional":true},{"name":"Transformers","optional":true},{"name":"XLA","optional":true}],"status":"live","first_seen_at":"2026-11-12T16:12:52Z","employer_posted_date":"2026-11-12","last_verified_at":"2026-11-12T23:00:47Z","board_verified":true,"closed_at":null,"days_open":0,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":0},"description":"AI Inference / Systems Software Architect\nReports To: VP, Engineering\nCompany Overview:\nNetlist, Inc. (OTCQB: NLST) is a leading provider of high-performance modular memory subsystems and next-generation storage-class memory solutions. We specialize in cutting-edge technologies that enable innovation in AI, cloud computing, and enterprise infrastructure. Our product portfolio includes DDR4/DDR5 DIMMs, NAND-based SSDs, and advanced interconnect technologies such as CXL and PCIe.\nJoin our world-class engineering team and be part of shaping the future of memory and storage architecture.\nPosition Summary:\nThis is a highly technical role for an individual who deeply understands AI Data Center and Edge AI Inference workloads, model execution, systems software, memory management, and hardware/software co-design.\nThe successful candidate will work closely with the Chief AI Systems Architect, AI Product Strategist, AI Hardware / Memory Systems Architect, and R&D engineering teams to understand how AI workloads execute on current infrastructure, identify software bottlenecks, and architect software that enables new hardware and memory technologies to deliver measurable customer value.\nWe are particularly interested in investigating opportunities involving AI workload, software stack, and inference runtime usage of the hardware to deliver the required performance and efficiency.\nKey Responsibilities:\nAI Inference Architecture\nDevelop a deep understanding of modern AI inference workloads and their system-level behavior\nAnalyze the execution characteristics of Large Language Models (LLMs), Generative AI, Agentic AI, Long-context inference, Mixture-of-Experts (MoE), Retrieval-Augmented Generation (RAG), Multimodal AI and Edge inference\nAnalyze the differences between prefill and decode workloads\nCharacterize the impact of batch size, sequence length, concurrency, model size, attention mechanisms, and memory access patterns\nIdentify whether workload bottlenecks are caused by compute, memory bandwidth, memory capacity, latency, interconnect, software overhead, or scheduling\nAI Runtime and Systems Software\nArchitect software infrastructure that allows AI workloads to efficiently utilize heterogeneous memory and compute resources\nAreas may include AI inference runtimes, model execution engines, scheduling, resource management, memory management, KV-cache management, data movement, prefetching, caching, model partitioning, load balancing, multi-device execution, distributed inference, accelerator orchestration and telemetry and performance monitoring\nEvaluate and contribute to open-source and commercial AI software stacks such as PyTorch, CUDA, ROCm, Triton, vLLM and other emerging inference runtimes and compiler frameworks\nAI Memory Management\nWork closely with the AI Hardware / Memory Systems Architect on next-generation memory architectures to make the entire memory hierarchy appear as an efficient, application-aware resource rather than a collection of independent storage tiers\nExplore how software can intelligently manage HBM, DDR, CXL memory, memory pools, disaggregated memory, NVMe, persistent storage, local versus remote memory, model weights, context state and KV cache\nDevelop policies and mechanisms for data placement, tiering, migration, caching, prefetching, eviction, compression, decompression, memory sharing, QoS, isolation and resource allocation\nHardware / Software Co-Design\nWork closely with the hardware architects to ensure that architectural features and hardware capabilities like CXL memory, memory pooling, smart memory controllers, near-memory compute, PIM, inference engines, AI accelerators, compression engines and specialized cache architectures can be effectively exposed and utilized by the software stack\nCollaborate on AI runtime architecture, memory management, KV-cache management, scheduling, data placement, prefetching, compression, workload orchestration, APIs and software interfaces and hardware telemetry and monitoring\nEnsure that hardware innovations translate into measurable application-level benefits rather than isolated component-level benchmarks\nDevelop and lead performance optimization methodologies based on real AI workloads. Measure and optimize tokens/sec, time-to-first-token (TTFT), time-per-output-token (TPOT), latency, throughput, memory bandwidth utilization, memory capacity utilization, accelerator utilization, power efficiency, cost per inference, cost per million tokens and system level TCO\nInference Performance Optimization\nIdentify opportunities to improve performance through kernel optimization, quantization, sparsity, compression, operator fusion, memory placement, scheduling, batching, speculative decoding, KV-cache optimization, prefill/decode optimization and communication reduction\nSoftware Architecture for CXL and Disaggregated Memory\nHelp define the software architecture necessary to make CXL-based memory expansion, pooling, and disaggregation practical for AI workloads\nInvestigate host memory versus CXL memory placement, shared versus dedicated memory, memory allocation policies, NUMA-aware scheduling, remote-memory latency, bandwidth allocation, memory QoS, memory migration, application-level\nDevelop software mechanisms that allow applications to benefit from additional capacity without unacceptable latency or performance penalties\nDevelop software architecture for AI context memory systems. Potential capabilities include KV-cache tiering, KV-cache compression, KV-cache quantization, prefix sharing, context reuse, cache eviction, context migration, session-aware caching, distributed context management, GPU-to-remote-memory transfers and context prefetching\nversus system-level control and multi-host memory orchestration\nAI Context / KV-Cache Software\nArchitecture Modeling and Prototyping\nDevelop software prototypes to validate new hardware architectures\nBuild workload models and emulation environments before silicon availability\nCreate benchmark suites representative of customer workloads\nEvaluate architecture concepts using existing CPUs, GPUs, FPGAs, or emulation platforms\nQuantify software overhead and expected system-level benefits\nEstablish performance baselines against existing GPU, CPU, CXL, and inference solutions\nRequired Qualifications:\nBachelor's or Master's degree in Computer Science, Computer Engineering, Electrical Engineering, or a related technical field; PhD is a plus\n10+ years of experience in systems software, AI infrastructure, computer architecture, inference systems, compilers, runtimes, or related areas\nDeep understanding of modern AI/ML inference workloads\nStrong systems programming skills, preferably in C/C++, Python, or comparable languages\nStrong understanding of computer architecture, memory systems, operating systems, and data movement\nExperience architecting or optimizing large-scale AI inference systems\nDemonstrated experience translating application/workload requirements into systems architecture\nStrong understanding of performance modeling and benchmarking\nExcellent communication skills and ability to work across hardware and software organizations\nPreferred Qualifications:\nExperience with several of the following:\nLLM inference\nTransformer architecture\nKV cache\nvLLM\nPyTorch\nCUDA\nTriton\nTensorRT\nROCm\nXLA\nMLIR / LLVM\nFlashAttention\nMoE\nQuantization\nSpeculative decoding\nDistributed inference\nGPU systems\nAI accelerators\nHBM\nDDR\nCXL\nNUMA\nMemory pooling / disaggregation\nPIM / near-memory computing\nAI networking\nAI storage\nEdge AI\nHardware/software co-design\nSalary Range: $275,000","description_format":"text","description_chars":7589,"description_truncated":false,"requirements":{"experience_years_min":10,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"bachelor","optional":false},"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["Digital Storage","Memory & Storage Chips"],"lifecycle":[{"event":"open","at":"2026-11-12T23:00:47Z"}],"visa":[],"liveness":{"score":86,"band":"hot","label":"Hiring now","p_open":1,"p_active":0.86,"p_room":1,"age_days":0,"expected_fill_days":18,"reasons":["conf:1","win:early"],"computed_at":"2026-11-13T00:42:26Z"},"pay":{"stated_usd_annual":275000,"is_top_pay":true},"html_url":"https://alion.io/job/netlist-ai-inference-systems-software-architect","json_url":"https://alion.io/job/netlist-ai-inference-systems-software-architect.json","meta":{"generated_at":"2026-11-13T00:42:26Z","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":1572,"day_limit":null,"remaining_today":null,"minute_limit":300,"resets_at":"2026-11-14T00:00:00Z"}},"offers":[{"id":"company.slices","title":"One company in depth, by slice","status":"live","price":{"credits":0.1,"usd":0.01,"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":691714},"rest":"https://alion.io/mcp/rest/get_company?id=691714"},"human":"https://alion.io/catalog?offer=company.slices&for=job%2Fnetlist-ai-inference-systems-software-architect"},{"id":"market.stats","title":"A market slice: pay, demand and time to fill","status":"free","price":{"credits":0,"usd":0},"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%2Fnetlist-ai-inference-systems-software-architect"},{"id":"job.search","title":"Open jobs by role, technology, place, pay and visa","status":"live","price":{"credits":0.1,"usd":0.01},"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%2Fnetlist-ai-inference-systems-software-architect"},{"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/netlist-ai-inference-systems-software-architect\", \"note\": \"what you need it for\"}"},"human":"https://alion.io/catalog?offer=company.verify&for=job%2Fnetlist-ai-inference-systems-software-architect"}],"agent":{"mcp":"https://alion.io/mcp/jobs","mcp_open":"https://alion.io/mcp/open","next":[{"tool":"get_job","arguments":{"id":4203473}},{"tool":"search_jobs","arguments":{"company":"netlist.com","detail":"compact"}},{"tool":"match_people","arguments":{"job_id":4203473},"note":"people open to offers who fit this vacancy"}],"note":"The same data through MCP tools: https://alion.io/mcp/open needs no sign-in (compact searches, postings, people); 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