Sr. Machine Learning Engineer, Responsible AI– Applied Research Science
About Pinterest: Millions of people around the world come to our platform to find creative ideas, dream about new possibilities and plan for memories that will last a lifetime. At Pinterest, we’re on a mission to bring everyone the inspiration to create a life they love, and that starts with the people behind the produ
What this role actually needs.
About Pinterest: Millions of people around the world come to our platform to find creative ideas, dream about new possibilities and plan for memories that will last a lifetime. At Pinterest, we’re on a mission to bring everyone the inspiration to create a life they love, and that starts with the people behind the produ Responsibilities: - Design and drive projects in the responsible AI frontier to identify, avoid, and mitigate bias across a wide range of ML applications at Pinterest. These include but are not limited to Gen AI product evaluations, foundation models safety fine tuning and alignment, and Red Teaming. - Collaborate with other engineering teams (trust and safety, ML Platform, Content Understanding, Search, Homefeed,) to leverage their platforms and signals and work with them to collaborate on the adoption and evaluation of Responsible AI practices and ML Fairness tooling across Pinterest. - Mentor junior engineers on the Responsible AI team and across the company on the R-AI space. - Work with the team and senior leaders at the company to define and drive technical strategy in this area. - 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, 2-tower architectures, LLMs and VLMS) and their applications in large-scale Search and Recommender Systems. 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, 2-tower architectures, LLMs and VLMS) and their applications in large-scale Search and Recommender Systems. - Proven ability to measure, deploy, and refine fairness interventions and broader Responsible AI solutions at scale, bridging state-of-the-art research with tangible product impact. - 4+ years working experience in the engineering teams that build large-scale ML-driven user-facing products - 1+ years experience leading cross-team engineering efforts. - Masters or PhD in Comp Sci or related fields Company context: Pinterest is the visual discovery platform that powers idea search and shopping across web and mobile.
Day-to-day expectations
Pinterest lists these responsibilities for the Sr. Machine Learning Engineer, Responsible AI– Applied Research Science role.
- Design and drive projects in the responsible AI frontier to identify, avoid, and mitigate bias across a wide range of ML applications at Pinterest. These include but are not limited to Gen AI product evaluations, foundation models safety fine tuning and alignment, and Red Teaming.
- Collaborate with other engineering teams (trust and safety, ML Platform, Content Understanding, Search, Homefeed,) to leverage their platforms and signals and work with them to collaborate on the adoption and evaluation of Responsible AI practices and ML Fairness tooling across Pinterest.
- Mentor junior engineers on the Responsible AI team and across the company on the R-AI space.
- Work with the team and senior leaders at the company to define and drive technical strategy in this area.
- 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, 2-tower architectures, LLMs and VLMS) and their applications in large-scale Search and Recommender Systems.
What a strong candidate brings
These requirements are extracted from the source listing and normalized for UpJobz readers.
- 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, 2-tower architectures, LLMs and VLMS) and their applications in large-scale Search and Recommender Systems.
- Proven ability to measure, deploy, and refine fairness interventions and broader Responsible AI solutions at scale, bridging state-of-the-art research with tangible product impact.
- 4+ years working experience in the engineering teams that build large-scale ML-driven user-facing products
- 1+ years experience leading cross-team engineering efforts.
- Masters or PhD in Comp Sci or related fields
Why this listing is more than a copied job post.
Sr. Machine Learning Engineer, Responsible AI– Applied Research Science is framed against UpJobz source checks, country scope, compensation visibility, and work-authorization signals so candidates can make a faster go/no-go decision.
United States tech market
United States roles on UpJobz are filtered for high-tech relevance, source freshness, and actionable employer detail before they are allowed into SEO surfaces.
Compensation read
The employer source does not expose a reliable salary range, so candidates should ask for compensation early instead of waiting until late-stage interviews.
Work authorization read
Current extracted signal: Open to TN, H-1B, and OPT candidates already in the United States. UpJobz treats this as a search signal, not legal advice, and links visa-sensitive roles back to the relevant visa hub where possible.
Location read
On-site roles in San Francisco should be compared against commute, local salary bands, and nearby employer demand.
Browse similar jobs
Turn this listing into an application plan.
This is the first pass at the premium UpJobz layer: a fast brief that helps serious applicants move with more clarity.
Next moves
- Tailor your resume around ai and llm instead of sending a generic application.
- Use the first two bullets of your application to connect your background directly to sr. machine learning engineer, responsible ai– applied research science is a high-signal on-site role in san francisco, and it is most realistic for open to tn, h-1b, and opt candidates already in the united states.
- Open the role quickly if it fits and bookmark three similar jobs before you leave the page.
Interview themes
Watchouts
- Compensation is hidden, so get range clarity in the first recruiter conversation.
- Use open to tn, h-1b, and opt candidates already in the united states as part of your positioning so the recruiter does not have to infer it.
- Show concrete examples of succeeding in on-site environments.
Keywords to match against your background
Use these terms to decide whether your resume, portfolio, and recent projects line up with the role.
Apply through the employer source
Open the source listing from pinterestcareers.com, confirm the role is still active, then apply on the employer or ATS page.
Source: pinterestcareers.com · Source ID: 7494938 · Confidence: 90/100 · Last checked: May 7, 2026
How UpJobz verifies job sourcesContinue browsing tech jobs