Machine Learning Engineer II, Responsible AI

Role overview An applied machine learning engineer is needed to advance fairness, ethics, and safety across a large-scale, multi-modal consumer platform serving hundreds of millions of users. The role sits on a horizontal Responsible AI team that partners across trust & safety, user modeling, and content understanding to ship user-facing fairness features and shape generative-AI safeguards.

Responsibilities - Execute projects at the responsible AI frontier, identifying, avoiding, and mitigating bias across ML applications including generative AI. - Collaborate with partner engineering teams to integrate Responsible AI practices, ML fairness tooling, and evaluation methods into shared platforms. - Mentor junior engineers within the team and across the broader organization on Responsible AI principles and techniques. - Partner with senior leaders to define and drive technical strategy for fairness, alignment, and ethical AI deployment. - Measure, deploy, and refine fairness interventions that translate state-of-the-art research into tangible product impact.

Requirements - Extensive, real-world experience applying advanced ML methods to production systems, with a strong track record in responsible technology spanning fairness, ethics, and broader societal considerations. - Deep familiarity with cutting-edge ML architectures (e.g., transformer-based models, two-tower architectures, LLMs) and their application to large-scale search and recommender systems. - 2+ years of experience on engineering teams that build large-scale, ML-driven user-facing products. - Master's or PhD in Computer Science or a related field.

Nice to have - Publications at top machine learning conferences. - Experience using AI coding assistants (e.g., Cursor, Copilot, Codex) for development, debugging, testing, and refactoring. - Familiarity with LLM-powered productivity tools for documentation search, experiment analysis, SQL/data exploration, and workflow acceleration. - Expertise in scalable real-time systems that process streaming data.

Benefits and work setup - Hybrid working model with periodic in-person collaboration; position is not eligible for relocation assistance. Base salary range $138,905–$285,982 USD plus equity, with final compensation based on location, experience, and skills.