{"id":3136938,"url":"https://alion.io/job/mercor-mlops-engineer-ai-systems","title":"MLOps Engineer - AI Systems","company":{"id":4960,"name":"Mercor","domain":"mercor.com","url":"https://alion.io/company/mercor","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":true,"listed_via":null,"ats_vendor":"Ashby","truth_index":{"grade":"B","score":84,"open_postings":16,"ghost_share":0,"stale_share":0.438,"repost_share":0,"time_to_fill_p50_days":65,"computed_at":"2026-10-27T05:46:45Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":"junior","employment_type":"part_time","work_mode":"remote","remote_scope":"stated_countries","remote_scope_basis":"board_field","remote_working_hours":null,"hiring_geo_confidence":"inferred","locations":["San Francisco, United States"],"countries":["US"],"hiring_countries":["US"],"hiring_countries_total":1,"salary":null,"salary_estimate":{"min_usd":138000,"max_usd":315000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":52},"experience_years_min":2,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AWS Trainium","optional":false},{"name":"CUDA","optional":false},{"name":"CUTLASS","optional":false},{"name":"FSDP","optional":false},{"name":"JAX","optional":false},{"name":"KV Cache","optional":false},{"name":"LLM","optional":false},{"name":"Megatron-LM","optional":false},{"name":"MLIR","optional":false},{"name":"PyTorch","optional":false},{"name":"SGLang","optional":false},{"name":"Stripe","optional":false},{"name":"TensorRT","optional":false},{"name":"TensorRT-LLM","optional":false},{"name":"TPU","optional":false},{"name":"Triton","optional":false},{"name":"vLLM","optional":false},{"name":"XLA","optional":false}],"status":"live","first_seen_at":"2026-10-23T06:19:06Z","employer_posted_date":null,"last_verified_at":"2026-10-23T06:19:06Z","board_verified":false,"closed_at":null,"days_open":4,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":4},"description":"About the job\nMercor connects elite creative and technical talent with leading AI research labs. Headquartered in San Francisco, our investors include Benchmark, General Catalyst, Peter Thiel, Adam D'Angelo, Larry Summers, and Jack Dorsey.\nPosition: MLOps Engineer, LLM Performance (Kernels, Profiling, Serving)\nType:\nContract\nCompensation:\n$90-$120/hour\nLocation:\nRemote\nCommitment:\n40 hours/week\nRole Responsibilities\nDesign challenging tasks across kernels, profiling, debugging, and inference serving. Write accurate, well-structured solutions to expose where frontier models fail on accelerator code.\nGuide research and engineering teams to close knowledge gaps and improve AI model performance on ML systems, compilers, and training infrastructure topics.\nEvaluate ML systems tasks and solutions. Provide clear written technical feedback that stands up to expert review.\nDevelop guidelines and detailed rubrics covering kernel optimization, profiler output interpretation, distributed systems reasoning, and serving throughput and latency trade-offs.\nCollaborate with other subject matter experts to keep training data consistent and accurate.\nQualifications\nMust-Have\n2+ years of hands-on professional experience in ML systems, ML infrastructure, model serving, or accelerator performance engineering.\n\nPractical experience in writing or optimizing custom kernels (Pallas, Triton, CUDA, CUTLASS), performance profiling and trace analysis (JAX/XLA profiler, Kineto, torch.profiler, Nsight), debugging distributed or accelerator-bound workloads, serving large language models at scale (vLLM, SGLang, TensorRT-LLM, JetStream, KV cache, paged attention, continuous batching).\nWorking production experience with JAX and/or PyTorch. Framework-level depth is a strong plus: custom operators, sharding and distributed training (pjit/shard_map, FSDP, Megatron, MaxText), or compiler and graph-level work (XLA/StableHLO, torch.compile, MLIR).\nExperience with modern accelerators such as TPU (v4 to v6e), H100, B200, Trainium or MI300, and the ability to reason about throughput, latency, and memory trade-offs.\nDemonstrable career progression.\nAbility to engage reliably for at least 40 hours/week during weekdays.\nStrong written communication skills and the ability to explain complex technical decisions clearly.\nCompensation & Legal\nHourly contractor\n\nPaid weekly via Stripe Connect\n\nApplication Process (Takes 20-30 mins to complete)\nUpload resume\nAI interview based on your resume\nSubmit form\nResources & Support\nFor details about the interview process and platform information, please check: https://talent.docs.mercor.com/welcome\nFor any help or support, reach out to: \nPS: Our team reviews applications daily. Please complete your AI interview and application steps to be considered for this opportunity.","description_format":"text","description_chars":2827,"description_truncated":false,"requirements":{"experience_years_min":2,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[{"name":"United States","iso":"US","kind":"country"}],"hiring_excludes":[],"relocation_offered":false,"industries":["Artificial Intelligence","Recruiting & Staffing","Freelance & Talent Marketplaces","AI Training Data & Annotation"],"lifecycle":[{"event":"open","at":"2026-10-23T06:19:06Z"}],"visa":[],"liveness":{"score":90,"band":"hot","label":"Hiring now","p_open":1,"p_active":0.903,"p_room":1,"age_days":3,"expected_fill_days":65,"reasons":["seen:3","velocity","win:early","comp:junior,brand"],"computed_at":"2026-10-27T05:46:45Z"},"pay":null,"html_url":"https://alion.io/job/mercor-mlops-engineer-ai-systems","json_url":"https://alion.io/job/mercor-mlops-engineer-ai-systems.json","meta":{"generated_at":"2026-10-27T14:07:39Z","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":2541,"day_limit":null,"remaining_today":null,"minute_limit":300,"resets_at":"2026-10-28T00:00:00Z"}},"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":4960},"rest":"https://alion.io/mcp/rest/get_company?id=4960"},"human":"https://alion.io/catalog?offer=company.slices&for=job%2Fmercor-mlops-engineer-ai-systems"},{"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%2Fmercor-mlops-engineer-ai-systems"},{"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%2Fmercor-mlops-engineer-ai-systems"},{"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/mercor-mlops-engineer-ai-systems\", \"note\": \"what you need it for\"}"},"human":"https://alion.io/catalog?offer=company.verify&for=job%2Fmercor-mlops-engineer-ai-systems"}]}