Product Engineer, AI Email Applications, Artificial Intelligence (AI) Required -
产品工程师，人工智能 (AI) 电子邮件应用程序 - 从家工作作为产品工程師，人工智能的电子邮件申请，你将在用户需求，模型能力和工程限制的交叉点上工作。产品工程学员将直接与机器学习 (ML) 和工程团队合作定义系统应该如何行为，我们如何测量它以及我们如何持续改善它。这是一个深入技术，实践中的角色。你预计会理解系统和技术决策。人工智能和机器学习是这个机会所需的。这一职位是100%远程。必须愿意做60分钟的编码评估。产品工程师责任：· 从模型行为到系统行为，用户体验等对人工智能 (AI) 能力的端到端要求定义。· 将模型功能，评价结果和技术限制转化为清晰的产品和系统决策。· 对质量，延迟，成本，可靠性，安全性和 UX 进行妥协。·与机器学习 (ML),后端和客户端工程师紧密合作在系统设计，评估和代上。· 在线测量表格，在线实验和人类反中定义和发展评估框架。· 建立明确的质量条点和反循环，以实现人工智能经验。·通过清晰的规范，优先级和强大的技术判断来推动执行。·识别故障模式并确保人工智能 (AI) 系统进行预测性行为，并优雅恢复。· 自有产品质量端到端，准确性，可靠性，有用性和用户信任。产品工程师结果：· 产品策略清楚地将人工智能能力与用户需求和公司优先事项相一致。· AI 功能提供了真正价值，可以理解，可预测和被用户信赖。· 在不确定的情况下，决策有效平衡质量，速度，成本和可靠性。· 路线图和优先事项是明确的，基于实际用户反的快速回复。· 团队均有协调性，专注力，并且能够在 AI 产品目标上执行最小摩擦的情况下。产品工程师资格：· 人工智能 (AI) 和机器学习 (ML) 的经验要求。·强大的计算机科学基础知识和系统设计技能。· 对现代机器学习的坚实的理解 (ML) 以及人工智能 ( AI) 系统如何在生产中表现。
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Product Engineer, AI Email Applications, Artificial Intelligence (AI) Required - Work From Home
As Product Engineer, AI Email Applications, you will work at the intersection of user needs, model capability, and engineering constraints. The Product Engineer will work directly with Machine Learning (ML) and engineering teams to define how the system should behave, how we measure it, and how we continuously improve it. This is a deeply technical, hands-on role. You are expected to understand the system and challenge technical decisions. Artificial Intelligence (AI) and Machine Learning (ML) are required for this opportunity. This position is 100% Remote.
MUST BE WILLING TO TAKE A 60 MINUTE CODING ASSESSMENT.
Product Engineer Responsibilities:
- Define end-to-end requirements for Artificial Intelligence (AI) capabilities, from model behavior to system behavior to user experience.
- Translate model capabilities, evaluation results, and technical constraints into clear product and system decisions.
- Make trade-offs across quality, latency, cost, reliability, safety, and UX.
- Work closely with Machine Learning (ML), backend, and client engineers on system design, evaluation, and iteration.
- Define and evolve evaluation frameworks across offline metrics, online experiments, and human feedback.
- Establish clear quality bars and feedback loops for AI-powered experiences.
- Drive execution through clear specifications, prioritization, and strong technical judgment.
- Identify failure modes and ensure Artificial Intelligence (AI) systems behave predictably and recover gracefully.
- Own product quality end-to-end, correctness, reliability, usefulness, and user trust.
Product Engineer Outcomes:
- Product strategy clearly aligns Artificial Intelligence (AI) capabilities with user needs and company priorities.
- AI features deliver real value, are understandable, predictable, and trusted by users.
- Decisions balance quality, speed, cost, and reliability effectively under uncertainty.
- Roadmaps and priorities are clear, with fast iteration based on real user feedback.
- Teams are aligned, focused, and able to execute on AI product goals with minimal friction.
Product Engineer Qualifications:
- Artificial Intelligence (AI) and Machine Learning (ML) experience required.
- Strong computer science fundamentals and system design skills.
- Solid understanding of modern Machine Learning (ML) and how Artificial Intelligence (AI) systems behave in production.
- Comfortable reading technical designs, understanding architectures, and engaging deeply with engineers.
- Strong intuition for model limitations, hallucinations, evaluation, and failure modes.
- Significant experience owning complex, technical products end-to-end.
- Hands-on experience with AI-powered products, particularly LLM-based systems.
- Experience with model evaluation, experimentation, prompting, or Artificial Intelligence (AI) system iteration.
- Ability to turn ambiguous problems into clear requirements, measurable outcomes, and executable plans.
- Strong judgment and the ability to make decisions when the right answer is not obvious.
- Highly technical, curious, and comfortable going deep.
- Strong bias toward shipping, experimentation, and learning from real-world usage.
- Able to challenge engineers and researchers constructively while maintaining strong collaboration.
- Comfortable operating with significant ownership in a fast-moving, zero-to-one environment.
- An engineering background is a strong plus, but what matters most is the ability to reason deeply about - both AI systems and product outcomes.
Nice to have:
- Experience shipping AI-heavy consumer products.
- Background as an engineer or highly technical product manager.
- Experience defining evaluation metrics for Machine Learning (ML) systems.
- Strong intuition for Artificial Intelligence (AI) UX patterns and failure handling.
- Prior experience in zero-to-one product environments.
Benefits include medical insurance, Dental, Vision, Savings Plan Options, PTO, etc.
Keywords: San Francisco CA Jobs, AI, Artificial Intelligence, AI Email Applications, LLM, Large Language Model, ML, Machine Learning, Product Engineer, UX, User Experience, Work From Home, Remote, California Recruiters, IT Jobs, California Recruiting
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Originally posted on Himalayas