Staff Product Manager (Buyer ML)

Location: Brooklyn, New York, US; hybrid work with attendance at the Brooklyn office once or twice per week for candidates within commuting distance. Remote candidates outside commuting distance may be considered case by case, with occasional travel to the office expected.

Salary: $201,000–$271,000 annual in Geo-1 locations; $180,000–$244,000 annual in Geo-2 locations.

Company

hirify.global operates a global marketplace for unique and creative goods, connecting independent sellers with buyers through commerce technology.

What you will do

• Build product strategy for buyer discovery and sequence ML work across multiple teams.
• Partner with engineering teams in Matching, Relevance, and Recommendations and align Buyer Experience teams on priorities and outcomes.
• Define buyer signals, improve signal collection, and translate buyer behavior data into ML opportunities.
• Partner with ML engineers and applied scientists to prioritize, build, evaluate, and launch retrieval, ranking, personalization, and recommendation solutions.
• Define outcome metrics beyond model quality and analyze analytics, research, and customer feedback to guide investment decisions.
• Lead prioritization and alignment across consuming teams, making tradeoffs visible to the VP and senior collaborators.

Requirements

• 6+ years of product management experience, with significant experience supplying ML-powered products in recommendations, search, personalization, or similar domains at a technology company.
• Deep understanding of retrieval systems, ranking models, embeddings, and recommendation pipelines sufficient for credible technical discussions with engineers and scientists.
• Strong analytical skills, including sizing ambiguous buyer problems, defining metrics and their limitations, and evaluating incremental ML value.
• Experience leading product work in a matrixed environment across engineering and product partners without shared reporting structures.
• Track record of testing the biggest risks first with lightweight tests and using evidence for Stop/Pivot/Proceed decisions.
• Strong A/B testing knowledge, including hypothesis formulation, metric selection, result interpretation, and experiment limitations.
• Experience aligning ML engineering, applied science, analytics, and research partners and earning engineering credibility through domain depth and decision-making.
• Experience originating strategy across multiple teams or consuming partners in ambiguous spaces.
• Commitment to continuous learning, sharing knowledge, and giving and receiving direct feedback.

Culture & Benefits

• Collaborative, cross-functional work with Engineering, Design, Research, Data Science, and Machine Learning.
• Work on buyer discovery and commerce experiences serving millions of buyers and sellers.
• Equity package and annual performance bonus.
• Competitive benefits supporting employees and their families.
• Hybrid work with office attendance expectations based on proximity to Brooklyn and occasional travel for eligible remote candidates.
• Visa sponsorship is supported, though availability may be limited to certain roles and skills.

Hiring process

• Submit a resume; a cover letter is optional.
• Workplace accommodations are available during the interview and hiring process upon request.