Machine Learning Engineer

About Pinterest
Millions of people around the world come to Pinterest 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 product. Discover a career where you ignite innovation for millions, transform passion into growth opportunities, celebrate each other's unique experiences, and embrace the flexibility to do your best work. Creating a career you love? It's possible.

About The Role
We are seeking a highly skilled Staff Machine Learning Engineer to join our Content Mining team. In this role, you will serve as the technical lead for a team of five engineers, including four Machine Learning Engineers (MLEs). Your primary responsibility will be to define and execute the multi‑quarter technical vision and roadmap for source discovery, content acquisition optimization, and understanding. You will be deeply involved in designing, training, and deploying advanced ML systems, particularly Large Language Models (LLMs) and NLP models, to power Pinterest's content extraction and classification capabilities. This position offers an exciting opportunity to lead innovative projects, influence cross-functional teams, and contribute to Pinterest's mission of inspiring creativity and discovery.

Qualifications

• 5+ years of experience in building end-to-end ML products, with at least 2 years in a technical leadership role.
• Deep hands-on expertise with NLP and LLM training and inference, using frameworks like PyTorch and Python.
• Proven track record of deploying models at scale, including feature and data pipelines, online serving, and monitoring.
• Strong software engineering skills in Python, adhering to best practices.
• Experience mentoring senior engineers and influencing cross-functional teams.
• Master's or PhD degree in Machine Learning, Computer Science, or related fields.
• Knowledge of LLM efficiency techniques such as LoRA/adapters, distillation, quantization, and prompt caching.
• Experience with MLOps tools and platforms like Airflow, Spark/Presto, Triton, and vLLM.
• Excellent problem-solving skills and ability to manage complex projects with multiple stakeholders.

Responsibilities

• Own the long-term architecture, roadmap, and execution strategies for content source discovery, acquisition optimization, and understanding.
• Lead design reviews, establish engineering standards, and facilitate cross-team alignment with Product, Data, and Infrastructure teams.
• Mentor and develop engineers through technical guidance, code reviews, and pairing sessions.
• Train and fine-tune LLMs and NLP models for classification, extraction, and instruction-following tasks.
• Design feature sharing frameworks and evaluate model performance through robust evaluation loops and guardrails.
• Productionize models for large-scale inference, optimizing for latency, reliability, and cost efficiency through techniques like quantization and caching.
• Establish evaluation metrics, run A/B tests, and manage automated regressions to ensure quality and performance.
• Collaborate with labeling teams to define data standards and improve data quality through feedback loops and weak supervision.
• Define and meet operational Service Level Objectives (SLOs) for data quality, model performance, and system reliability.
• Lead incident response efforts, postmortem analyses, and continuous improvement initiatives to enhance operational excellence.
• Measure and drive the downstream impact of ML initiatives on revenue and user engagement.

Benefits

• Competitive salary and comprehensive health benefits.
• Flexible work arrangements with remote work options.
• Opportunities for professional growth and development.
• Collaborative and inclusive company culture.
• Access to cutting-edge technology and innovative projects.
• Paid time off and wellness programs.

Equal Opportunity

Pinterest is an equal opportunity employer and makes employment decisions based on merit. We are committed to creating an inclusive environment for all employees and applicants. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, gender expression, national origin, age, marital status, veteran status, disability, or any other protected characteristic under applicable law.