Senior machine learning engineer building recommendation and personalization systems for Pinterest’s creative discovery platform. Improving ML models across Homefeed, Ads, Growth, Shopping, and Search.
About the role
- Machine Learning Fellow contributing to Scale AI’s Human Frontier Collective, which advances human-centered frontier AI. Designing, evaluating, and optimizing models while co-authoring research.
Responsibilities
- Participate in an interdisciplinary expert network focused on advancing frontier AI
- Work on selected AI/ML projects with Scale AI and affiliated labs and platforms
- Build AI safety and policy guardrails
- Design, review, and optimize PyTorch models
- Evaluate complex ML code and AI-generated implementations for efficiency and correctness
- Evaluate AI models and design experiments
- Build reinforcement-learning environments
- Co-author technical reports and research papers with Scale’s research team
- Get matched regularly to selected partner projects
- Discuss research experience, professional background, and mission alignment during the interview process
Requirements
- PhD, or postdoctoral research experience, in Machine Learning, Computer Science, or a related field; or senior industry experience in Machine Learning or a related field
- Strong proficiency in Python and modern ML frameworks, including PyTorch and TensorFlow
- Experience with cloud infrastructure such as AWS
- Experience with MLOps tools such as Docker
- Experience with LLM frameworks such as LangChain is a plus
- Detail-oriented, innovative thinker with a passion for applied AI research and a commitment to collaboration
- Must have or independently obtain full-time work authorization in the country of residence
- Scale AI does not sponsor visas for Fellows
Benefits
- Fully remote opportunity with no fixed end date; engagements continue as long as there's mutual interest
- Flexible schedule with no minimum commitment; fellows set their own schedules
- Community network access, including newsletters, discussion channels, virtual sessions, IRL events, and more
- Opportunities to co-author technical reports and research papers
- Competitive project pay rates
- Most fellows spend 10–25 hours per week
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