Sr. Tech Ai/Ml Product Manager

OverviewAbout JobHire.AI JobHire.AI is building a vertical AI agent that automates job search for professionals.We help thousands of users land interviews by finding, tailoring, and applying to jobs on their behalf — at scale and with precision.We are profitable, growing fast, and now entering a phase of deep product refinement and organic growth through exceptional UX and perceived value.Mission JobHire.AI is a personal AI agent for continuous professional development and happiness at work.About The RoleWe are seeking a highly analytical and hands-on Senior Tech AI/ML Product Manager with deep expertise in Machine Learning and Artificial Intelligence and Product Management.You will define and build a best-in-class job discovery and matching engine that connects users with the most relevant roles for them, at scale.You will own the strategy, discovery, and delivery of AI-powered features, focusing on matching, ranking, and personalization systems.The ideal candidate is an entrepreneurial thinker with an engineering mindset, capable of building rapid prototypes, making decisive calls with imperfect data, and relentlessly driving measurable outcomes.Key ResponsibilitiesStrategy & Ownership: Define the vision, strategy, and roadmap for AI/ML product features (JobHunt Engine).Take full ownership of the product lifecycle from hypothesis to scaled impact, focusing on business results, not just model performanceML Product Leadership: Translate business problems into ML hypotheses and solutions.Work side-by-side with ML engineers and data scientists to define data requirements, evaluation frameworks (evals, RAG, agents), model monitoring, and delivery processesHypothesis Validation & Experimentation: Design and execute rapid, pragmatic validation cycles.Formulate clear hypotheses (Problem ? Mechanism ? Impact ? Metric), choose the right validation method (A/B test, shadow model, phased rollout), and make data-driven go/no-go decisions under uncertainty.Be scrappy and effective with limited data or infrastructureStructured Problem Solving: Apply critical thinking to decompose complex, ambiguous problems.Cut through noise, prioritize what truly matters, and build simple, effective solutions firstCross-Functional Execution: Collaborate closely with Engineering, Data Science, and business teams.Communicate complex ML concepts clearly and align stakeholders on goals, trade-offs, and progressExpected OutcomesFirst 3 MonthsEstablish baseline measurement of job supply coverage across the U.S. market, including companies listed in the NASDAQ-100Increase the percentage of users who successfully find a job through the platform by 50%, driven by improvements in matching logic and job relevanceFirst 6 MonthsExpand job vacancy coverage in the U.S. market, achieving up to 80% coverage of NASDAQ-100 companies and increasing overall coverage by 30%Ship a major upgrade to the resume enhancement featureIncrease the percentage of users who successfully found a job through our platform by 3×12 MonthsFurther expand U.S. job vacancy coverage, achieving a 50% increase in coverage of NASDAQ-100 companies compared to the 6-month baselineDouble the matching success rate, measured as the percentage of matched vacancies approved as relevant by usersImprove the application-to-offer conversion rate by 50%, directly impacting the core business outcome — successful employmentRequirementsTechnical & ML Expertise:Strong understanding of ML/LLM fundamentals (NLP, recommendation systems, etc.)Hands-on experience building and scaling AI-powered features (matching, ranking, personalization)Practical knowledge of modern AI/ML concepts: evaluation frameworks, RAG, agents, model monitoringAbility to define data pipelines, metrics, and work processes with ML engineering teamsNice to have: hands-on experience in a Data Science, Data Analyst, or ML Engineer roleProduct Development:5+ years of experience in a Product Manager role, preferably in a data-intensive or ML-driven domain (HRTech experience is a strong plus)Proven ability to formulate and rigorously test product/ML hypotheses using statistical methods (A/B testing, significance, confidence intervals)Ability to reason about probability, causality, and data limitations to make informed decisionsMindset & Approach:Entrepreneurial & Hands-on: "Let\'s build it" attitude. Able to create quick prototypes and test ideas without over-engineering. Comfortable with "building with sticks and glue" to learn fastOutcome-Oriented: Owns the business result, not just the AI model.Pragmatic and willing to simplify or kill features that don\'t drive impactThrives in Ambiguity: Can navigate uncertainty, contradictory model results, and noisy data.Structured thinker who can bring clarity to complex situations.Communication: Fluent English and Russian.Excellent ability to communicate with technical (Engineers, Data Scientists) and non-technical stakeholdersOur Ideal CandidateThinks simultaneously about business metrics and model quality metricsHas a super-engineer mindset coupled with an entrepreneurial, "get things done" approachTakes responsibility for the end result, not just the AI modelDoesn\'t fall in love with technology but stays focused on solving the problemTheir first reaction to an idea is "Let\'s go build and test it."Hiring ProcessHR Introduction CallTeam InterviewsProduct challengeReference CheckBenefitsJobHire.AI is a mission-driven, fastest-growing, and profitable global companyAmazing opportunity to build Job Hunt Engine, shaping the future of AI HRtech, people\'s careers and livesBrilliant team of the strongest A players from McKinsey, Nexters, Gett, GlovoRemote work - work/life balanceCompetitive package ($*******k, based on experience and location)38 days Off (vacation + local holidays) and sick leave#J-*****-Ljbffr