Note: The job is a remote job and is open to candidates in USA. Pinterest is hiring a Staff Machine Learning Engineer to build complex machine learning models and systems for growth content ranking, especially notification content. The role leads technical direction and owns the production ML stack, including model improvements, infrastructure health, and cross-functional collaboration.
Responsibilities
- Lead multiple technical sub-areas within Growth content science effectively
- Drive Growth ML model improvements through AB test driven innovation loop - from ideation to production launches
- Own the health of our ML ecosystem: training pipelines, feature and serving infrastructure, evaluation frameworks and monitoring, AB test set up, etc
- Help raise the technical excellence bar through mentorship, reviews, evaluations, documentation, standard setting, etc
- Collaborate and build strong working relationships with colleagues and stakeholders to tackle big, cross-functional, initiatives
- Work closely with other engineering leaders to form technical directions and roadmaps
- Operate autonomously, take ownership in complex and evolving environments and drive work effectively
- Identify and apply relevant state-of-the-art techniques from recent research and/or collaborate on novel research directions
- Continuously optimize various parts of work by building and using cutting-edge AI tools
Skills
- Graduate degree in Computer Science or in a related field
- Minimum of 8 years of experience in machine learning engineering, including hands-on experience building and shipping models for a large-scale, real-time, end-user production recommender system
- Expertise in recommender modeling, including sequence modeling of user behavior with transformer architectures, DNN rankers and generative and LLM-native recommenders
- Experience in building and operating high-QPS, latency-constrained ML systems, including training and serving infrastructure, and in owning the cost, latency and reliability tradeoffs
- Experience in industry-grade software engineering that others use as the example, and in conducting thorough code and design reviews that raise the quality of a team's work
- Understanding of content personalization and content quality as one problem, and of why cold-start and low-signal users break standard rankers
- Experience in leading technical work across teams, making timely decisions on hard tradeoffs and saying no when the user experience or the system health is at stake
- Experience in mentoring junior engineers
- Outstanding written and verbal communication skills, especially in a cross-functional set up
- Demonstrated experience using AI to improve speed and quality in applied research
- Strong track record of publications and patents
Benefits
- Eligible for equity.
- Can be situated anywhere in the country; in-office collaboration 1-2 times/quarter.
Company Overview
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