обновлено 1 день назад
Member of Technical Staff, Lead Researcher (AI)
203 500 - 299 300$
Мэтч & Сопровод
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Описание вакансии
Текст:
TL;DR
Member of Technical Staff, Lead Researcher (AI): Building publishable AI research and frontier systems for DoorDash's large-scale local commerce marketplace with an accent on agentic logistics, foundation models, reinforcement learning, evaluation, multimodal understanding, and embodied AI. Focus on setting the research agenda, leading projects from problem framing through publication and production deployment, and building the research organization.
Location: San Francisco, CA or Sunnyvale, CA, United States
Salary: $203,500–$299,300 USD annually, plus potential equity grants.
Company
operates a large-scale, multi-sided local commerce marketplace connecting consumers, merchants, and delivery workers.
What you will do
- Set the research agenda for one or more areas of AI Research.
- Lead high-impact research projects from problem framing through publication and, where appropriate, production deployment.
- Define research culture and operating practices, including publication standards, collaboration with product teams, and the balance between open and proprietary research.
- Interview, recruit, mentor, and develop researchers, engineers, and fellows.
- Partner with ML platform, product, and operations teams to identify high-leverage research opportunities and translate findings into real-world impact.
Requirements
- Strong research track record, including first-author publications at top ML venues or equivalent systems, open-source work, or research artifacts adopted at scale.
- Experience leading ambitious research projects end-to-end and producing results that others build on.
- Ability to work with real systems and real-world data, not only benchmarks.
- Excellent written and verbal communication skills and experience mentoring or developing researchers.
- Interest in hiring, agenda-setting, culture-building, and cross-functional collaboration as part of a founding research team.
- A PhD in a relevant field is typical but not required; demonstrated research output and judgment are prioritized.
Nice to have
- Experience with agentic systems for logistics, long-horizon planning, tool use, multi-agent coordination, or agent evaluation.
- Experience with transfer reinforcement learning, continual learning, foundation models, marketplace forecasting, pricing, matching, or personalization.
- Experience with multimodal systems, robotics, embodied AI, or physical-world data collection.
Culture & Benefits
- Access to proprietary marketplace data, scalable data collection, high compute budgets, and full research infrastructure.
- Support for publication at leading research venues and collaboration with academic researchers, fellows, and visiting researchers.
- Direct access to leadership and autonomy to operate at a principal-level research scope.
- Comprehensive benefits for regular employees, including 401(k) matching, medical, dental, and vision coverage, paid parental leave, paid time off, paid sick leave, and 11 paid holidays.
- Additional wellness, commuter, disability, life insurance, family-forming assistance, and mental health benefits.
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