Product Manager, Core Models

About the Role

The Core Models team is responsible for building data flywheels, evaluations, and measurement systems to ensure that AI models have strong capabilities and behavior. This role requires a deep understanding of AI models, their limitations, and their potential applications. The successful candidate will have a unique opportunity to work on cutting-edge technologies and contribute to the development of AI models that can positively impact society.

What You Will Do

• Translate user and product goals into clear model requirements, system architecture choices, and research priorities across query understanding, indexing, retrieval, ranking, tool boundaries, data, training, inference, and evaluation.
• Build closed learning loops that turn product usage, explicit feedback, and other user signals into datasets, evaluations, experiments, training priorities, and launch decisions.
• Define success across offline evaluations and online product metrics, balancing model quality, usefulness, latency, safety, reliability, and cost.
• Partner closely with post-training research, applied product engineering, Model Design, and Data Science to integrate capabilities into the mainline model stack.
• Create reusable platforms and operating systems for evaluation, experimentation, and signal collection so that new capabilities improve faster over time.
• Use concrete product failures and emerging user needs to identify gaps, form hypotheses, and shape the next wave of research and product investment.
• Develop and maintain a deep understanding of AI models, their strengths, weaknesses, and potential applications.
• Collaborate with cross-functional teams to ensure that AI models are aligned with user needs and business goals.
• Stay up-to-date with the latest developments in AI research and industry trends, applying this knowledge to improve AI models and their applications.

What We Are Looking For

• Deep expertise in product management or closely related experience, including ownership of technically complex products or platforms.
• Deep fluency in one or more relevant domains: search and information retrieval, recommendation or personalization systems, ML platforms, large-scale data systems, model evaluation, or AI product infrastructure.
• Ability to pair offline evaluation with online experimentation and user signals, and distinguish a useful metric from a convenient one.
• Technical depth, crisp judgment, and a willingness to engage directly with the details to earn the trust of researchers and engineers.
• Combination of consumer product taste with systems rigor, and care about both the quality people feel and the infrastructure that makes it repeatable.
• Ability to move quickly in ambiguous environments, communicate directly, and help teams make sound decisions without waiting for perfect information.
• Passion for how increasingly capable models affect people, and humility, judgment, and a strong sense of responsibility to the work.
• Excellent communication and collaboration skills, with the ability to work effectively with cross-functional teams.
• Strong problem-solving skills, with the ability to analyze complex problems and develop creative solutions.

Nice to Have

• Experience working in a hybrid remote work environment and familiarity with remote collaboration tools.
• Knowledge of AI ethics and safety considerations, with a focus on creating beneficial and safe AI experiences.
• Familiarity with agile development methodologies and version control systems.
• Experience with data analysis and visualization tools, with the ability to extract insights from complex data sets.

Benefits and Perks

• Competitive salary and equity package.
• Opportunity to work on cutting-edge AI technologies and contribute to the development of AI models that can positively impact society.
• Collaborative and dynamic work environment with a team of experienced professionals.
• Flexible working hours and remote work options.
• Access to cutting-edge technologies and tools.
• Professional development opportunities, including training and education programs.
• Comprehensive health insurance and retirement plan.
• Generous paid time off and holidays.

• Tip: When applying for this role, make sure to highlight your experience in product management, particularly in AI or related fields. Emphasize your ability to work in a fast-paced, ambiguous environment and your passion for creating safe and beneficial AI experiences.
• Tip: To stand out as a candidate, build a portfolio that showcases your accomplishments in product management, including any experience with AI models or related technologies. Share this portfolio during the interview process to demonstrate your expertise.
• Tip: During the interview, be prepared to discuss your understanding of AI models, their limitations, and their potential applications. Show a willingness to learn and adapt to new technologies and trends in the AI industry.
• Tip: When negotiating salary, consider the total compensation package, including equity and benefits, rather than just the base salary. Research the market rate for similar positions to ensure you are fairly compensated.
• Tip: Be aware of the potential red flags in the company culture or the role itself. Ask questions during the interview process to understand the company's values, mission, and expectations. Ensure that they align with your own values and career goals.
• Tip: Stay up-to-date with the latest developments in AI research and industry trends. This will not only make you a more competitive candidate but also prepare you for the challenges and opportunities that come with working in the AI field.
• Tip: Consider the hybrid remote work environment and the company's approach to collaboration and communication. Make sure you are comfortable working in this setup and that it aligns with your work style and preferences.