{"id":761007,"url":"https://alion.io/job/omnifold-mts-ml-research-engineer","title":"MTS - ML Research Engineer","company":{"id":679044,"name":"Omnifold","domain":"omnifold.ai","url":"https://alion.io/company/omnifold","size_band":"51-200","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Ashby","truth_index":{"grade":"C","score":67,"open_postings":11,"ghost_share":0.545,"stale_share":0,"repost_share":0,"time_to_fill_p50_days":null,"computed_at":"2026-10-12T06:55:09Z"}},"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":["San Francisco, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":171000,"max_usd":326000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":1124},"experience_years_min":5,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Function Calling","optional":false},{"name":"LLM","optional":false},{"name":"Machine Learning","optional":false},{"name":"Time Series Forecasting","optional":false},{"name":"Tool Use","optional":false}],"status":"live","first_seen_at":"2026-04-01T21:53:33Z","employer_posted_date":"2026-04-01","last_verified_at":"2026-10-12T20:37:29Z","board_verified":true,"closed_at":null,"days_open":194,"trust":{"level":"ghost","repost_count":0,"flags":["stale","company_stale"],"days_open":193},"description":"Member of Technical Staff, ML Research Engineer\nOmnifold trains custom AI models for each customer's supply chain - purpose-built systems that forecast demand, optimize decisions, and adapt continuously to a changing world. The research team is responsible for the core intelligence that makes this possible: developing new model architectures, curating proprietary data assets, and pushing the boundaries of what ML can do.\nWhat makes this job interesting:\nYou will work on problems that frontier models can't solve. Supply chain dynamics require modeling physical systems and processes.\n\nYou will own the full research cycle, from hypothesis to production model, with direct visibility into real-world impact.\n\nYou will work at the intersection of machine learning models, optimization, LLM reasoning capabilities, and proprietary data - a combination few research teams are building\n\nWhat you'll own:\nTraining models for forecasting and optimization across complex, multi-variable supply chain environments\n\nBuilding and curating proprietary data assets that carry signal about real-world physical and commercial systems\n\nIntegrating LLM knowledge and reasoning capabilities into purpose-built models to maximize accuracy and adaptability\n\nContinuously improving model performance as market conditions shift (consumer sentiment, product launches, geopolitical changes, competitive dynamics)\n\nWhat we're looking for:\n5+ years of industry machine learning engineering, including and experimentation\n\nExperience with time-series forecasting, mathematical modeling, optimization, or related domains\n\nUnderstanding of LLMs, including fundamentals and practical system design including tool use and eval design\n\nExperience working with messy, heterogeneous real-world data\n\nExperience working with large code bases\n\nAcademic or industry research experience preferred\n\nComfort operating in a fast-moving, early-stage environment where research directly feeds production systems\n\nLocation: San Francisco (in-person, 5 days per week)\nOmnifold’s Mission\nEvery bad forecast has a physical consequence. Unnecessary goods are manufactured, shipped, and stored. Emergency air freight is needed for misallocated products. Poor production planning means workers show up with nothing to do, or work frantic overtime. Inefficiency is everywhere.\nOur mission is to eliminate waste and accelerate growth for every company with physical products.","description_format":"text","description_chars":2428,"description_truncated":false,"requirements":{"experience_years_min":5,"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":["Artificial Intelligence","Supply Chain AI"],"lifecycle":[{"event":"open","at":"2026-09-11T18:29:21Z"}],"visa":[{"country":"US","licensed_sponsor":true,"evidence":"H-1B filings in 12 months: 1","filings_12m":1,"filings_prev_12m":0,"green_card_filings_12m":0,"median_offered_wage_usd":192500,"route":null,"cap_exempt":false,"checked_at":"2026-10-03T21:08:04+00:00","sources":["US Department of Labor: LCA disclosure data (H-1B, H-1B1, E-3)"],"filings_for_role_12m":1}],"liveness":{"score":5,"band":"cold","label":"Long shot","p_open":1,"p_active":0.195,"p_room":0.28,"age_days":193,"expected_fill_days":37,"reasons":["conf:2","stale_co","ghost","win:tail","crowd:"],"computed_at":"2026-10-12T06:55:09Z"},"pay":null,"html_url":"https://alion.io/job/omnifold-mts-ml-research-engineer","json_url":"https://alion.io/job/omnifold-mts-ml-research-engineer.json","meta":{"generated_at":"2026-10-13T00:09:15Z","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":252,"day_limit":null,"remaining_today":null,"minute_limit":300,"resets_at":"2026-10-14T00:00:00Z"}},"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":679044},"rest":"https://alion.io/mcp/rest/get_company?id=679044"},"human":"https://alion.io/catalog?offer=company.slices&for=job%2Fomnifold-mts-ml-research-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%2Fomnifold-mts-ml-research-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%2Fomnifold-mts-ml-research-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/omnifold-mts-ml-research-engineer\", \"note\": \"what you need it for\"}"},"human":"https://alion.io/catalog?offer=company.verify&for=job%2Fomnifold-mts-ml-research-engineer"}]}