{"id":3952537,"url":"https://alion.io/job/a16z-speedrun-founding-ml-engineer","title":"Founding ML Engineer","company":{"id":4398864,"name":"a16z speedrun","domain":"speedrun.a16z.com","url":"https://alion.io/company/a16z-speedrun","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":true,"listed_via":null,"ats_vendor":null,"truth_index":null},"role":"AI/ML","role_family":"AI/ML","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":["San Francisco, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":null,"experience_years_min":10,"visa_sponsorship":true,"relocation_package":false,"has_equity":true,"technologies":[{"name":"AWS","optional":false},{"name":"MQTT","optional":false},{"name":"Time Series","optional":false}],"status":"live","first_seen_at":"2026-11-09T04:35:14Z","employer_posted_date":null,"last_verified_at":"2026-11-09T04:35:14Z","board_verified":false,"closed_at":null,"days_open":0,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":0},"description":"About the Company\nPhilyron is building the predictive brain for commercial fleets from tankers, cargo ships to defense vessels. We use real-time sensor data and historical maintenance records to predict and explain engine failures before they happen.\nThe Role\nWe're hiring a founding ML engineer to own the AI systems at the heart of the product. You'll work directly with the founders and own the full loop: data, training, evals, and shipping models into production.\nWhat You'll Do\nConnectivity - get data off the ship. Ships have terrible, intermittent connectivity. You'll build the pipeline that moves sensor data from a vessel's edge device to our cloud reliably over satellite links (VSAT / Starlink) - using lightweight, fault-tolerant protocols (MQTT / Sparkplug B), with encryption in transit and graceful handling of connections that drop for days at a time and resume.\nCloud backbone - land it and make it usable. You'll stand up our cloud architecture (AWS): a real-time \"hot path\" that checks incoming sensor metrics against safety thresholds and fires instant alerts, and a \"cold path\" that stores high-frequency time-series data for trend analysis and model training. You'll also build the integration layer that pulls decades of historical maintenance records out of operators' existing CMMS databases - the data that makes our predictions possible.\nPredictive fusion engine - the reason we win. This is the heart of it. You'll build the ML system that fuses two data streams almost no competitor combines: live sensor signatures and historical failure records. You'll map past maintenance events to the sensor patterns that preceded them, train anomaly-detection and failure-prediction models (e.g. isolation forests / autoencoders for anomalies, gradient-boosted trees / LSTMs for remaining-useful-life), and design the fleet-wide-plus-per-vessel modeling approach that makes predictions both accurate and personalized to each engine. The output isn't \"anomaly detected\" - it's \"this pattern preceded a gearbox bearing failure across the fleet; inspect within 14 days.\"\nAutomated reporting. You'll build the service that compiles trends, history, and predictions into clean reports delivered to operators on a schedule - turning the platform into something that shows up in their inbox and proves its value every week.\n\nWhat We're Looking For\nEvidence you've shipped ML that real users touched - in production, research, or serious projects\n\nShow us projects, repos, demos, side projects - real things you've designed and built end to end, ideally ones that touched both data/ML and the infrastructure around it. Your portfolio is your résumé.\n\nStrong fundamentals across the stack, not just notebooks\n\nPragmatism: you pick the boring approach that works over the clever one that might\n\nComfort owning systems end to end with no ML team behind you\n\nCompensation & Equity\nEarly-stage compensation: 130 ~ 150k salary, ~1.5% \nexperience and location - we're happy to talk through the details early in the process.","description_format":"text","description_chars":3029,"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":["Equity"],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":[],"lifecycle":[{"event":"open","at":"2026-11-09T04:52:34Z"}],"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":32,"reasons":["seen:0","win:early"],"computed_at":"2026-11-09T06:03:00Z"},"pay":null,"html_url":"https://alion.io/job/a16z-speedrun-founding-ml-engineer","json_url":"https://alion.io/job/a16z-speedrun-founding-ml-engineer.json","meta":{"generated_at":"2026-11-10T00:17:03Z","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":587,"day_limit":null,"remaining_today":null,"minute_limit":300,"resets_at":"2026-11-11T00:00:00Z"}},"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":4398864},"rest":"https://alion.io/mcp/rest/get_company?id=4398864"},"human":"https://alion.io/catalog?offer=company.slices&for=job%2Fa16z-speedrun-founding-ml-engineer"},{"id":"market.stats","title":"A market slice: pay, demand and time to fill","status":"live","price":{"credits":2,"usd":0.2},"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%2Fa16z-speedrun-founding-ml-engineer"},{"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%2Fa16z-speedrun-founding-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/a16z-speedrun-founding-ml-engineer\", \"note\": \"what you need it for\"}"},"human":"https://alion.io/catalog?offer=company.verify&for=job%2Fa16z-speedrun-founding-ml-engineer"}],"agent":{"mcp":"https://alion.io/mcp/jobs","mcp_open":"https://alion.io/mcp/open","next":[{"tool":"get_job","arguments":{"id":3952537}},{"tool":"search_jobs","arguments":{"company":"speedrun.a16z.com","detail":"compact"}},{"tool":"match_people","arguments":{"job_id":3952537},"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); https://alion.io/mcp with an Alion account has everything. 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