Key Responsibilities
– End-to-End Product Building: Own the full product lifecycle. Translate ambiguous model capabilities into polished, user-centric products. Define user journeys, craft intuitive UX/UI for AI interactions, and manage Go-to-Market (GTM) strategies.
– Vision & Strategy: Define the product vision and roadmap for frontier AI models, guiding them from early-stage experimental research to scalable systems that solve real-world user problems.
– Research Translation: Partner intimately with world-renowned research scientists and engi neers to identify commercial, consumer, and scientific applications for state-of-the-art break throughs.
– Hands-on Technical Execution: Utilize your proficiency in Python to build rapid prototypes, interact with model APIs, run data analysis, script evaluation pipelines, and occasionally dive into PyTorch/JAX code to deeply understand model behavior.
– Model Evaluation & Alignment: Design rigorous quantitative and qualitative evaluation metrics. Work closely with safety and alignment teams to ensure models are robust, unbi ased, and safe for broad deployment.
– Cross-Functional Leadership: Lead complex, multi-disciplinary initiatives across research, engineering, design, legal, and marketing teams to ensure successful product launches.
Minimum Qualifications
– Experience: 8 to 10 years of total experience in product management, engineering, or re search science, with at least 4+ years explicitly leading AI/ML, Deep Learning, or cutting-edge data products.
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– Technical Proficiency: Strong, demonstrable coding skills in Python. You must be comfort able writing scripts for data analysis (Pandas, NumPy), interacting with ML frameworks, and building quick functional prototypes via Jupyter notebooks or similar environments.
– Domain Expertise: Deep conceptual understanding of modern machine learning paradigms (e.g., Transformers, Reinforcement Learning, Generative AI). You can easily read and under stand advanced AI research papers.
– 0-to-1 Product Building: Proven track record of taking highly ambiguous technologies from concept to successful launch, including defining UX, crafting user stories, and driving user adoption and engagement.
– Communication: Exceptional ability to translate dense, highly complex technical concepts into clear product requirements, intuitive design specs, and strategic narratives for diverse audiences.
Preferred Qualifications
– Advanced degree (MS or PhD) in Computer Science, Artificial Intelligence, Mathematics, Physics, or a related quantitative field.
– Prior experience working in a pure AI research laboratory or deeply embedded within an applied research team.
– Hands-on experience with large-scale model evaluation, RLHF (Reinforcement Learning from Human Feedback), or AI safety protocols.
– Contributions to open-source ML projects or published research in relevant AI conferences (NeurIPS, ICML, ICLR).
We are an equal opportunity employer committed to fostering a diverse, inclusive, and collaborative environment where the brightest minds can tackle the world’s toughest challenges.