{"id":667198,"url":"https://alion.io/job/rhoda-senior-inference-optimization-ml-engineer","title":"Senior Inference Optimization ML Engineer","company":{"id":685148,"name":"Rhoda AI","domain":"rhoda.ai","url":"https://alion.io/company/rhoda","size_band":"501-1000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Ashby","truth_index":{"grade":"A","score":95,"open_postings":42,"ghost_share":0,"stale_share":0,"repost_share":0,"time_to_fill_p50_days":78,"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":["Mountain View, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":175000,"max":250000,"currency":"USD","period":"year","gross":null,"usd_annual":250000},"salary_estimate":null,"experience_years_min":3,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AWQ","optional":false},{"name":"CUDA","optional":false},{"name":"CUDA Toolkit","optional":false},{"name":"JAX","optional":false},{"name":"Knowledge Distillation","optional":false},{"name":"Model Distillation","optional":false},{"name":"Multimodal AI","optional":false},{"name":"PyTorch","optional":false},{"name":"Quantization","optional":false},{"name":"TensorRT","optional":false},{"name":"TorchServe","optional":false},{"name":"Triton","optional":false},{"name":"vLLM","optional":false},{"name":"World Models","optional":false},{"name":"XLA","optional":false},{"name":"LLM","optional":true},{"name":"Speculative Decoding","optional":true}],"status":"live","first_seen_at":"2026-05-12T14:45:29Z","employer_posted_date":"2026-05-12","last_verified_at":"2026-10-17T20:57:07Z","board_verified":true,"closed_at":null,"days_open":158,"trust":{"level":"ok","repost_count":0,"flags":["company_stale"],"days_open":157},"description":"At Rhoda AI, we’re building the next generation of generalist intelligent robots. We own the full robotics stack from high-performance hardware and robot systems to the infrastructure and state-of-the-art foundation world models that control our robots. Our robots are designed to be generalists capable of operating in complex, real-world environments and handling long-tail edge cases, made possible by our cutting edge research and end-to-end system design. We've raised over $450M and are investing aggressively in model research, infrastructure, hardware development, and manufacturing scale-up to make generalist robotics a reality.\nWe're looking for an Inference Optimization MLE to help build and operate the systems that make our foundation models run fast and efficiently in production. You'll be responsible for squeezing maximum performance out of large multimodal models, across cloud and on-robot deployment targets. You will working closely with research and robotics teams to close the gap between training and real-world deployment.\nWhat You'll Do\nOwn inference performance end-to-end - diagnose and improve latency, throughput, and efficiency of large foundation models in production\n\nBuild systematic performance attribution: latency decomposition (compute vs. memory bandwidth vs. I/O), bottleneck identification, and prioritization across model families\n\nApply and develop optimization techniques including quantization, pruning, distillation, operator fusion, and model compilation (e.g., TensorRT, torch.compile, XLA)\n\nOptimize attention mechanisms, KV caching, and memory layouts for large multimodal models (vision, video, language, proprioception)\n\nWork with kernel-level tooling (e.g., CUDA, Triton) to identify hotspots and implement or tune custom kernels where needed\n\nBuild benchmarking and regression detection infrastructure: latency baselines, throughput curves, and automated detection of performance regressions across model versions\n\nCollaborate closely with research engineers to translate model innovations into optimized, deployment-ready implementations\n\nWhat We're Looking For\n3+ years of experience in inference optimization, ML systems, or a closely related field\n\nDeep hands-on experience with modern ML stacks (PyTorch required; JAX a plus)\n\nStrong understanding of compute, memory bandwidth, and I/O bottlenecks in large model inference\n\nExperience with model optimization techniques: quantization (INT8/FP8/AWQ), distillation, pruning, and compilation\n\nFamiliarity with inference serving frameworks (e.g., Triton, TensorRT, vLLM, TorchServe)\n\nExceptional debugging and measurement ability: turn \"inference is slow\" into clear bottlenecks, experiments, and validated improvements\n\nHigh ownership mindset and comfort in a fast-moving environment\n\nNice to Have (But Not Required)\nGPU kernel or compiler-level experience (CUDA, Triton, graph capture, operator fusion)\n\nExperience with multimodal or video model inference (variable-length sequences, packing/bucketing)\n\nFamiliarity with edge/cloud hybrid deployment patterns and on-robot inference constraints\n\nExperience with speculative decoding, continuous batching, or other LLM serving optimizations\n\nBackground in streaming or low-latency systems relevant to real-time robot control\n\nWhy This Role\nDirect leverage on research velocity and real-world robot performance - every efficiency gain you make accelerates model iteration and tightens the loop between model and robot behavior\n\nOwn the optimization layer that determines how quickly and efficiently our foundation models run in the real world - high ownership, high impact, small elite team","description_format":"text","description_chars":3646,"description_truncated":false,"requirements":{"experience_years_min":3,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["Industrial Robotics","Humanoid Robots"],"lifecycle":[{"event":"open","at":"2026-09-10T22:05:03Z"}],"visa":[{"country":"US","licensed_sponsor":true,"evidence":"H-1B filings in 12 months: 6","filings_12m":6,"filings_prev_12m":1,"green_card_filings_12m":0,"median_offered_wage_usd":252500,"route":null,"cap_exempt":false,"checked_at":"2026-10-15T11:24:14+00:00","sources":["US Department of Labor: LCA disclosure data (H-1B, H-1B1, E-3)"],"filings_for_role_12m":2}],"liveness":{"score":21,"band":"cold","label":"Long shot","p_open":1,"p_active":0.738,"p_room":0.28,"age_days":157,"expected_fill_days":78,"reasons":["conf:1","velocity","win:tail","crowd:"],"computed_at":"2026-10-17T05:46:00Z"},"pay":{"stated_usd_annual":250000,"is_top_pay":true},"html_url":"https://alion.io/job/rhoda-senior-inference-optimization-ml-engineer","json_url":"https://alion.io/job/rhoda-senior-inference-optimization-ml-engineer.json","meta":{"generated_at":"2026-10-17T23:02:32Z","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":1256,"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":685148},"rest":"https://alion.io/mcp/rest/get_company?id=685148"},"human":"https://alion.io/catalog?offer=company.slices&for=job%2Frhoda-senior-inference-optimization-ml-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%2Frhoda-senior-inference-optimization-ml-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%2Frhoda-senior-inference-optimization-ml-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/rhoda-senior-inference-optimization-ml-engineer\", \"note\": \"what you need it for\"}"},"human":"https://alion.io/catalog?offer=company.verify&for=job%2Frhoda-senior-inference-optimization-ml-engineer"}]}