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Вакансия из Hirify Global, списка международных tech-компаний Для мэтча и отклика нужен Plus
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У роли понятная зона ответственности от исследования потребностей до запуска продукта, а компания хорошо финансирована и работает над AI-инструментами для data science; главный нюанс - нужны и сильный продуктовый опыт, и практические знания data science.
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Широкий профильПередний край AIСильная поддержкаЧёткая ответственностьУважение к границам
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Описание вакансии
Текст:
Hirify AI/Оригинал
TL;DR
Product Manager (AI): Building self-serve data science products, AI agents, and MLOps workflows around the NEXUS large tabular model with an accent on customer discovery, predictive ML workflows, and transparent agent interactions. Focus on defining product roadmaps, translating NEXUS capabilities into usable experiences, and helping data scientists manage and monitor model quality in production.
Location: EU, Remote
Company
hirify.global is an AI research lab developing NEXUS, a large tabular model for enterprise decision-making and predictive machine learning.
What you will do
Own and lead the roadmap and product decisions for data science products from customer discovery through definition, launch, and iteration.
Work directly with data scientists to understand their needs, workflows, and usage patterns.
Shape AI agents and data science tools across the platform, balancing intuitive workflows with flexibility for technical users.
Define how users guide agents, inspect their work, and understand results while preserving transparency and control.
Own customer workflows for managing and monitoring predictive model quality in production through MLOps.
Define success measures for usability, adoption, and customer outcomes using usage data, evaluations, and user feedback.
Requirements
4+ years of experience owning and shipping ML or data science products with an engineering team, from discovery and roadmap decisions through delivery and iteration.
2+ years of hands-on data science experience, including classification, regression, and time series analysis.
Experience working with structured or tabular data and predictive ML workflows.
Experience building agentic products, with practical understanding of their limitations and interaction patterns that help users trust and control them.
Strong customer discovery skills, including uncovering underlying problems, testing assumptions, and translating findings into product decisions.
Technical fluency and strong collaboration skills with engineers and applied data scientists, including the ability to turn ambiguity into clear, deliverable scope.
Data-driven prioritization grounded in usage data, evaluation results, and user evidence.
Nice to have
Earlier client-facing data science experience followed by ownership of a product developed with an engineering team.
Experience building internal data science tools for Applied AI, solutions teams, or other technical customer-facing teams.
Experience working in an early-stage AI company with direct exposure to enterprise customers or a forward-deployed motion.
Culture & Benefits
Competitive compensation with salary and equity.
Comprehensive health coverage for employees and dependents.
Paid parental leave for all new parents, including adoptive and surrogate journeys.
Relocation support for employees moving to one of the company's office locations.
High-trust, low-ego culture valuing diversity of thought, ownership, initiative, personal boundaries, and varied working styles.
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