2 дня назад
AI Product Manager
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
AI Product Manager (LLM/AI): Building a proactive smart assistant for conversations, errands, organization, and workflows with an accent on long-running workflows, persistent context, tool use, and reliable real-world task completion. Focus on defining AI system requirements, designing evaluation frameworks, balancing quality, latency, cost, and reliability, and shipping predictable, trustworthy AI features.
Location: Remote, United States
Company
is building a proactive AI assistant for everyday users to support conversations, errands, organization, and workflows.
What you will do
- Define end-to-end AI system requirements spanning model capabilities, product behavior, and user impact.
- Translate model capabilities, data constraints, and evaluation results into product and system decisions.
- Make trade-offs across quality, latency, cost, reliability, and user experience.
- Collaborate with ML, backend, mobile, and engineering teams on system design, evaluation, and iteration.
- Define evaluation frameworks using offline metrics, online experiments, and human feedback.
- Own product quality, including correctness, predictability, reliability, and user trust.
Requirements
- Strong computer science fundamentals, including algorithms, data structures, and system design.
- Solid understanding of ML fundamentals and modern AI systems in production.
- Hands-on experience with AI-powered products, including LLM-based systems.
- Experience with model evaluation, prompt or pipeline iteration, and feedback loops.
- Significant experience owning complex technical products end-to-end and working with senior engineers and ML teams.
- Strong judgment in ambiguous, fast-moving environments and the ability to balance technical and operational constraints.
Nice to have
- Experience shipping AI-heavy consumer products.
- Engineering or highly technical product management background.
- Experience defining evaluation metrics for ML systems.
- Experience with AI UX patterns, failure handling, and zero-to-one product development.
Culture & Benefits
- Small, high-talent-density, hands-on team.
- Collective decision-making and rapid execution.
- Emphasis on high-quality work, learning, structure, independent execution, and practical AI impact.
- Remote work with interviews conducted through virtual meetings and/or onsite meetings.
Hiring process
- Applications are evaluated by technical team members.
- Selected candidates complete three, and no more than four, interviews.
- A prompt hiring decision follows the interview process.
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