Opportunity at
PinterestStaff Machine Learning Engineer, Shopping Ads
Pinterest operates a digital platform that helps users worldwide find inspiration, plan projects, and discover new ideas. The company is currently hiring a Staff Machine Learning…
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About This Role
Pinterest operates a digital platform that helps users worldwide find inspiration, plan projects, and discover new ideas. The company is currently hiring a Staff Machine Learning Engineer, Shopping Ads to join its Merchant team on a full-time basis. In this on-site role, the selected candidate will act as the first machine learning engineering hire within the organization, serving as the technical lead and reporting directly to a Director. The position…
Job Description
Pinterest operates a digital platform that helps users worldwide find inspiration, plan projects, and discover new ideas. The company is currently hiring a Staff Machine Learning Engineer, Shopping Ads to join its Merchant team on a full-time basis. In this on-site role, the selected candidate will act as the first machine learning engineering hire within the organization, serving as the technical lead and reporting directly to a Director.
The position focuses on developing artificial intelligence and machine learning architectures, including large language models, aimed at recognizing and elevating high-quality merchants across the platform. Key initiatives involve agentic workflows, merchant integrity, brand affinity modeling, and enhancing shopping discovery for both organic and paid surfaces. The professional in this role will drive technical strategy from prototyping to production while balancing performance, cost, and safety.
This opportunity is well-suited for a seasoned engineer with a strong background in leading zero-to-one machine learning projects and shaping operational standards. The position requires working from an office 1 to 2 times per month, requiring candidates to live within commutable distance of San Francisco, Palo Alto, or Seattle. Qualified applicants should possess extensive technical experience in applied machine learning, system design, and cross-functional collaboration.
Responsibilities
- Manage technical delivery for cross-functional initiatives across problem framing, architecture, strategy, implementation, monitoring, and iteration.
- Collaborate with a Director and cross-functional leads to define technical direction, milestones, sequencing, and quality bars.
- Build and improve machine learning and generative artificial intelligence systems for merchant quality, content enrichment, attribute extraction, and entity resolution.
- Create robust evaluation and measurement frameworks including golden datasets, human-in-the-loop reviews, regression testing, and metric alignment.
- Design production systems considering quality, latency, reliability, cost, and safety guardrails.
- Establish organizational operating models for machine learning engineering, covering evaluation standards and launch readiness reviews.
- Partner with product, engineering, data science, design, legal, and platform teams to translate ambiguous needs into concrete deliverables.
- Drive experimentation through A-B tests and holdouts, conducting error analysis to improve user trust and shopping outcomes.
- Mentor team members on technical design, evaluation rigor, and production readiness while supporting future hiring and onboarding efforts.
Requirements
- Minimum of eight years of industry experience in machine learning engineering, applied machine learning, or software engineering.
- Meaningful time operating at a staff-level or equivalent individual contributor capacity delivering complex production systems.
- Demonstrated history of leading zero-to-one machine learning and large language model efforts from ambiguous concepts to production.
- Track record of shipping machine learning systems in domains like ranking, retrieval, recommendations, commerce, or ads relevance.
- Hands-on experience developing production-ready large language model applications or adjacent generative artificial intelligence systems.
- Deep background in evaluation, dataset strategy, labeling operations, and metric design.
- Strong system design skills for data- and machine-intensive architectures balancing scalability, cost, and reliability.
- Ability to commute to the San Francisco, Palo Alto, or Seattle offices for in-person collaboration 1 to 2 times per month.
Qualifications
- Bachelor’s degree in Computer Science, Engineering, or a related technical field, or equivalent practical experience.
Core Skills
Benefits
- Equity eligibility
Frequently Asked Questions
What is the employment type for this role?
This is a full-time position.
What is the remote or office work policy?
This is an on-site role that requires working from the office 1 to 2 times per month for collaboration. Candidates must live within commutable distance of San Francisco, Palo Alto, or Seattle.
What is the salary range for this position?
The base salary range for United States-based applicants is $222,716 to $389,753 USD, and the position is also eligible for equity.
Is relocation assistance provided?
No, this position is not eligible for relocation assistance.
Sample Interview Questions
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