- Страна
- Канада
- Зарплата
- 230 000 $ – 260 000 $
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Senior Product Manager – Data & Quality
Отличная вакансия в топовом AI-стартапе с высокой зарплатой, сильной инженерной культурой и возможностью работать над передовыми технологиями (GenAI, Agents).
Сложность вакансии
Высокая сложность обусловлена необходимостью глубоких технических знаний в области LLM, агентных систем и синтетических данных, а также опытом управления сложными кросс-функциональными проектами.
Анализ зарплаты
Предлагаемая зарплата ($230k - $260k) находится на верхней границе рыночного диапазона для Senior PM в Сан-Франциско, что отражает высокую техническую сложность роли.
Сопроводительное письмо
I am writing to express my strong interest in the Senior Product Manager – Data & Quality position at Snorkel AI. With over 6 years of experience in product management and a deep technical background in machine learning, I have consistently focused on the intersection of data quality and model performance. My experience building MLOps platforms and managing complex data labeling workflows aligns perfectly with Snorkel's mission to transform expert knowledge into specialized AI.
At my previous role, I led the development of an automated evaluation framework that reduced model iteration time by 40%. I am particularly drawn to Snorkel's research-driven approach and your focus on agentic data systems. I am confident that my ability to bridge the gap between Research, Engineering, and Operations will allow me to contribute immediately to the evolution of your Expert Contributor Quality and Evaluation products.
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Описание вакансии
About Snorkel
At Snorkel, we believe meaningful AI doesn’t start with the model, it starts with the data.
We’re on a mission to help enterprises transform expert knowledge into specialized AI at scale. The AI landscape has gone through incredible changes between 2015, when Snorkel started as a research project in the Stanford AI Lab, to the generative AI breakthroughs of today. But one thing has remained constant: the data you use to build AI is the key to achieving differentiation, high performance, and production-ready systems. We work with some of the world’s largest organizations to empower scientists, engineers, financial experts, product creators, journalists, and more to build custom AI with their data faster than ever before. Excited to help us redefine how AI is built? Apply to be the newest Snorkeler!
The Role
We are seeking a highly technical and strategic Senior Product Manager with deep AI/ML expertise to lead development across our agentic data systems, synthetic data systems, evaluations, and data-acceleration initiatives. This role is ideal for someone with a core ML/AI product background, strong familiarity with model development workflows, and demonstrated success delivering product experiences that improve the speed, quality, and scalability of data operations. You will work closely with Research, Engineering, Data Operations, and Design to define product vision, roadmap, and execution plans for intelligent workflow systems that optimize data pipelines, improve task quality, and enable faster and more efficient delivery of AI-ready datasets.
This is a highly cross-functional, technically deep IC role with broad surface area and significant impact. You will lead initiatives spanning multiple teams, balancing near-term execution with long-term platform evolution.
What You’ll Do
- Own the product vision, strategy, and roadmap for the task and Expert Contributor Evaluations product supporting internal and external platform users.
- Identify bottlenecks and lead cross-team efforts to improve overall quality and customer acceptance rate.
- Lead Evaluation products and tools across research, engineering, operations, and forward deployed engineers to drive excellence in product quality.
- Define, build, and set up continuous monitoring for performance metrics of Evaluations to improve their adaption, usage, and effectiveness.
- Own the strategy and execution of Expert Contributor Quality
- Build a recommendation system for optimal matching of ECs to tasks on the Snorkel Platform
- Work with cross-functional stakeholders to support enablement and adaptation initiatives of the Evaluations and Quality products
- Balance short-term delivery with long-term platform investments to support future growth.
Minimum Qualifications
- 5–7 years of experience as a Product Manager, with ownership of complex, cross-functional product areas.
- Educational background in computer science or related engineering practice
- Strong technical literacy across ML models, Gen AI concepts, LLM-based products, Agentic designs, evaluation, labeling strategies, and quality frameworks.
- Proven ability to drive deeply technical roadmaps end-to-end, from concept to launch.
- Ability to write clear PRDs, partner on research experimentation frameworks, and drive measurable outcomes.
- Experience building internal or platform-level products with complex workflows and multi-stakeholder environments.
- Proven ability to own end-to-end product experiences across multiple user personas.
- Strong analytical and problem-solving skills, with a track record of metrics-driven decision making.
- Excellent collaboration skills and experience partnering closely with Engineering, Research, and Operations teams.
Preferred Qualifications
- 5-7 years of experience as a Product Manager, including 3+ years focused on ML/AI products, MLOps, or data systems products.
- Experience with agent-based systems, generative AI, reinforcement learning, self-improving systems, or automated workforce/task routing platforms.
- Familiarity with LLMs, LLM Evaluations, human-in-the-loop systems, and synthetic data generation.
- Background in Machine Learning, Data Engineering, or related technical field
- Demonstrated ability to lead large, cross-team initiatives without formal authority.
Salary Range
$230,000—$260,000 USD
Be Your Best at Snorkel
Joining Snorkel AI means becoming part of a company that has market proven solutions, robust funding, and is scaling rapidly—offering a unique combination of stability and the excitement of high growth. As a member of our team, you’ll have meaningful opportunities to shape priorities and initiatives, influence key strategic decisions, and directly impact our ongoing success. Whether you’re looking to deepen your technical expertise, explore leadership opportunities, or learn new skills across multiple functions, you’re fully supported in building your career in an environment designed for growth, learning, and shared success.
Snorkel AI is proud to be an Equal Employment Opportunity employer and is committed to building a team that represents a variety of backgrounds, perspectives, and skills. Snorkel AI embraces diversity and provides equal employment opportunities to all employees and applicants for employment. Snorkel AI prohibits discrimination and harassment of any type on the basis of race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state, or local law. All employment is decided on the basis of qualifications, performance, merit, and business need.
We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodation.
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Навыки
- Product Management
- Machine Learning
- Generative AI
- LLM
- MLOps
- Data Engineering
- Synthetic Data
- Reinforcement Learning
- Agentic Systems
- Data Quality
Возможные вопросы на собеседовании
Проверка понимания специфики продукта Snorkel AI и роли качественных данных.
Как бы вы подошли к приоритизации функций в системе оценки качества данных, когда требования исследователей (Research) конфликтуют с операционными ограничениями (Operations)?
Оценка технической экспертизы в области современных ИИ-архитектур.
Какие метрики вы считаете ключевыми для оценки эффективности агентных систем (agentic systems) при подготовке обучающих данных?
Проверка опыта работы с человеческим фактором в ML-цикле.
Опишите ваш опыт разработки систем рекомендаций для сопоставления задач и экспертов (Expert Contributors). С какими основными проблемами вы сталкивались?
Оценка навыков работы с данными и аналитического мышления.
Как вы планируете выстраивать систему непрерывного мониторинга качества для синтетических данных, чтобы избежать деградации моделей?
Проверка лидерских качеств и влияния без формальной власти.
Расскажите о случае, когда вам пришлось убеждать команду инженеров или исследователей изменить технический вектор развития продукта. Каков был результат?
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- Страна
- Канада
- Зарплата
- 230 000 $ – 260 000 $