2 дня назад
Technical Product Manager (AI)
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Technical Product Manager (AI): Building a proactive AI 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 evaluation frameworks, balancing quality, latency, cost, reliability, and UX, and translating model capabilities into dependable product behavior.
Location: Remote, Singapore
Company
is building a proactive AI assistant for everyday users, focused on conversations, errands, organization, workflows, and reliable real-world task completion.
What you will do
- Define end-to-end AI system requirements spanning model capability, product behavior, and user impact.
- Translate model capabilities, data constraints, and evaluation results into product and system decisions.
- Balance quality, latency, cost, reliability, and user experience trade-offs.
- Work with ML, backend, and mobile engineers on system design, evaluation, and iteration.
- Define evaluation frameworks using offline metrics, online experiments, and human feedback.
- Own product quality, correctness, predictability, user trust, and reliable execution.
Requirements
- Strong computer science fundamentals, including algorithms, data structures, and system design.
- Solid understanding of machine learning 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 closely with senior engineers and ML teams.
- Strong judgment, prioritization, and ability to balance ambition with technical and operational reality.
Nice to have
- Experience shipping AI-heavy consumer products.
- Background as an engineer or highly technical product manager.
- Experience defining evaluation metrics for ML systems.
- Experience with AI UX patterns, failure handling, and zero-to-one product environments.
Culture & Benefits
- Work with a small, high-talent-density, hands-on team.
- Make collective decisions and move rapidly while balancing quality with learning.
- Work independently, bring structure, and exercise judgment in ambiguous environments.
- Remote work with interviews conducted virtually and/or onsite.
- Expect a streamlined process of three to four interviews and a prompt decision.
Hiring process
- Applications are evaluated by technical team members.
- Complete three, and no more than four, interviews via virtual meetings and/or onsite.
- Receive a prompt decision after the interview process.
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