{"id":25806,"url":"https://alion.io/job/liquidai-product-manager","title":"Product Manager","company":{"id":14548,"name":"Liquid AI","domain":"liquid.ai","url":"https://alion.io/company/liquid-ai","size_band":"201-500","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Ashby","truth_index":{"grade":"A","score":95,"open_postings":22,"ghost_share":0,"stale_share":0,"repost_share":0,"time_to_fill_p50_days":178,"computed_at":"2026-10-16T05:45:00Z"}},"role":"Product","role_family":"Product","seniority":null,"employment_type":"full_time","work_mode":"hybrid","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["San Francisco, United States","Boston, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":155000,"max_usd":325000,"period":"year","method":"role_country_seniority_unknown","sample_n":6157},"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Fine-tuning","optional":false},{"name":"LLM","optional":false},{"name":"AI Agents","optional":true},{"name":"Edge AI","optional":true}],"status":"live","first_seen_at":"2026-06-24T18:41:38Z","employer_posted_date":"2026-06-24","last_verified_at":"2026-10-16T23:21:56Z","board_verified":true,"closed_at":null,"days_open":114,"trust":{"level":"ok","repost_count":0,"flags":["company_stale"],"days_open":113},"description":"About Liquid AI\nSpun out of MIT CSAIL, we build general-purpose AI systems that run efficiently across deployment targets, from data center accelerators to on-device hardware, ensuring low latency, minimal memory usage, privacy, and reliability. We partner with enterprises across consumer electronics, automotive, life sciences, and financial services. We are scaling rapidly and need exceptional people to help us get there.\nThe Opportunity\nWe're hiring a Product Manager to drive specific product bets from idea to product-market fit.\nThis is a hands-on, ground-level role: you own an experiment, or a small set of them, get the product into real users' hands, and iterate toward PMF, working shoulder to shoulder with our ML, inference, and engineering teams to turn their energy into crisp, executable direction.\nIt is not a traditional SaaS PM role: the model and the product are inseparable, our core offering is customization & fine-tuning rather than prompt-only use, and real model depth is a prerequisite.\nWhat We're Looking For\nWe need someone who:\nFocus-giver: You turn high-energy, unfocused ideas into tight, executable product direction that engineers can build against.\n\nEvidence over intuition: You put products in front of real users early and let honest feedback drive decisions.\n\nTechnically fluent and AI-native: You hold your own with ML and inference engineers, know when an LFM is the right tool, and use AI & coding tools to prototype and test hypotheses yourself.\n\nConviction without stubbornness: You hold a clear point of view, update it in light of evidence, and can hit the ground running with light support.\n\nThe Work\nOwn one or more active product experiments end-to-end and drive them toward product-market fit.\n\nTurn vague, high-energy ideas into tight, executable product requirements that engineers can build against.\n\nPut the product in real users' hands early, gather genuine feedback, and iterate.\n\nRuthlessly prioritize: decide what to build now, what to defer, and what to kill.\n\nWork closely with ML, inference, and engineering teams, and flex across bets as priorities shift.\n\nDesired Experience\nMust-have:\nDirect, hands-on ML or applied LLM experience: you have built or trained models, you know the difference between prompting and fine-tuning in practice, and you know when an LFM is the right tool.\n\nA strong bias for action: you use AI and coding tools to prototype and test hypotheses yourself, so your insights are higher-signal than a PM who ran deep research once.\n\nDemonstrated ownership of product direction and prioritization, not just execution against a handed-down roadmap.\n\nThe ability to turn an ambiguous idea into a concrete, buildable plan, with light support rather than heavy coaching.\n\nNice-to-have:\nEnterprise product expertise: the focus and execution it takes to bring a new enterprise product to market and win in enterprise.\n\nExperience at an AI/ML company or on AI-powered products.\n\nFamiliarity with edge or on-device inference, agentic harnesses, evals, or observability.\n\nWhat Success Looks Like (Year One)\nYou own a bet end to end and take it from an ambiguous opportunity to a validated, or confidently killed, product direction backed by real user evidence.\n\nThe engineers you support move faster because your requirements are crisp and well-prioritized.\n\nYou have established a repeatable way to get products in front of users and turn their feedback into decisions.\n\nWhat We Offer\nFocused ownership: You drive a product bet end to end rather than owning a sliver of a large platform.\n\nCompensation: Competitive base salary with equity in a unicorn-stage company.\n\nHealth: We pay 100% of medical, dental, and vision premiums for employees and dependents.\n\nFinancial: 401(k) matching up to 4% of base pay.\n\nTime Off: Unlimited PTO plus company-wide Refill Days throughout the year.","description_format":"text","description_chars":3860,"description_truncated":false,"requirements":{"experience_years_min":null,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":false,"languages":[]},"benefits":["Equity","Unlimited PTO"],"hiring_locations":[{"name":"United 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