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AI Research & Product Strategy Lead – Handshake AI
Company | Handshake |
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Location | San Francisco, CA, USA |
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Salary | $200000 – $300000 |
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Type | Full-Time |
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Degrees | PhD |
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Experience Level | Senior, Expert or higher |
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Requirements
- Advanced degree (PhD preferred) or equivalent experience in Machine Learning, Computer Science, or related fields.
- Hands-on experience with LLMs and proficiency in frameworks like PyTorch, JAX, or TensorFlow.
- Track record of publishing in top ML venues (ACL, EMNLP, NAACL, NeurIPS, ICML, ICLR, COLM, etc.) or equivalent real-world research impact.
- Exceptional communication skills, comfortable presenting complex technical topics to audiences ranging from C-suite to PhD-level researchers.
- Ability to empathize with customer needs, influence decision-makers, and drive internal alignment on strategic priorities.
- Proven capacity to define problems, propose solutions, and execute effectively in fast-moving, high-stakes contexts.
- Strong bias toward action and a willingness to innovate beyond traditional product playbooks.
- Comfort debugging ML models and iterating on experiments at scale.
- Familiarity with cloud technology stacks (AWS, GCP, or similar) and ability to handle data workflows or ML pipelines in a production environment.
Responsibilities
- Serve as Handshake’s primary liaison to leaders at frontier AI labs.
- Maintain active communication channels with AI researchers and technical buyers.
- Dig beyond the surface of customer requests to uncover unarticulated needs.
- Bridge the gap between technical buyers and the product team.
- Define and prioritize roadmaps addressing tough questions in AI talent.
- Collaborate with engineering and operations to scope, prototype, and launch solutions that push the boundaries of AI evaluation and deployment.
- Translate AI research challenges into clear product objectives.
- Stay current with the AI/ML research landscape and turn cutting-edge ideas into proof-of-concepts.
- Work with engineering, operations, and business teams to deliver end-to-end solutions, from concept through production.
Preferred Qualifications
- PhD preferred in Machine Learning, Computer Science, or related fields.