Hiring: Product Manager Company: Liquid AI Location: San Francisco, CA Job Posted Time: 2026-09-03 07:38:16 Target Skills & Keywords : Fine-tuning, LLM, SaaS About the job Experience: •Direct, 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. •A 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. •Demonstrated ownership of product direction and prioritization, not just execution against a handed-down roadmap. •The ability to turn an ambiguous idea into a concrete, buildable plan, with light support rather than heavy coaching. Required Skills: •This 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. •It 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. •Focus-giver: You turn high-energy, unfocused ideas into tight, executable product direction that engineers can build against. •Evidence over intuition: You put products in front of real users early and let honest feedback drive decisions. •Technically 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. •Conviction without stubbornness: You hold a clear point of view, update it in light of evidence, and can hit the ground running with light support. •Own one or more active product experiments end-to-end and drive them toward product-market fit. •Turn vague, high-energy ideas into tight, executable product requirements that engineers can build against. Qualifications: •Enterprise product expertise: the focus and execution it takes to bring a new enterprise product to market and win in enterprise. •Operational familiarity with edge or on-device inference, agentic harnesses, evals, or observability. •What Success Looks Like (Year One) •You 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. •The engineers you support move faster because your requirements are crisp and well-prioritized. •You have established a repeatable way to get products in front of users and turn their feedback into decisions. Interested candidates, please apply directly through the job posting on company's career page or try via AI auto apply on this platform. Don't miss this opportunity to join a forward-thinking team!