ML Platform Scientist II: Production Pipelines & Causal ML

Pinterest; California (MO); Hybrid; USD 120,000 - 235,000; Full time

Benefits offered by this job

Equity

Job summary

Pinterest is seeking an experienced Data & Applied Scientist to advance the science and systems behind ML measurement and causal inference at scale. You will own end-to-end design of production ML systems and collaborate cross-functionally to turn research into durable platform capabilities.

The role requires building tools that multiply the impact of the ML organization, with an emphasis on production readiness, scalability, and rigorous methodology.

Qualifications

• 2+ years of hands-on experience as an applied scientist, ML engineer, research scientist or software engineer with ML production experience.
• Strong Python skills; experience with PyTorch or equivalent DL frameworks; familiarity with distributed compute (Spark, Ray). Ray is a strong plus.
• Enthusiasm for building tools and platforms that multiply the impact of an entire ML organization.
• Deep ML theory knowledge with strong fundamentals to reason about ML models from first principles.
• Proficiency in software development best practices including version control, code review, and reproducible ML pipelines.
• Experience with workflow management tools (Airflow, Prefect, Jenkins, or similar) for ML pipeline orchestration.
• Bachelor’s/Master’s degree in CS or equivalent experience.

Responsibilities

• Translate research-grade DS workflows into production ML pipelines using Airflow, WandB & Ray while establishing reusable patterns for other teams.
• Apply and productionize causal inference methods using the production ML stack (propensity scoring, IPW, TMLE) to address high-stakes measurement questions; build self-serve tooling for non-experts.
• Partner with ML engineers and product teams to identify opportunities for improved tooling, metrics, and measurement methods, unlocking step-change improvements.
• Leverage Pinterest's metadata and engagement signals to build data-driven frameworks from feature importance to content deindexing that improve efficiency.
• Design and build centralized ML platform tooling to improve feature and model creation, evaluation, and trust for daily-scale production.

Skills

Python

PyTorch

Ray

Spark

ML production

Software development

Education

Bachelor’s/Master’s degree in Computer Science

Tools

Airflow

WandB

Jenkins

Prefect

Spark

Job description

Pinterest is seeking an experienced Data & Applied Scientist to advance the science and systems behind ML measurement and causal inference at scale. You will own end-to-end design of production ML systems and collaborate cross-functionally to turn research into durable platform capabilities.

The role requires building tools that multiply the impact of the ML organization, with an emphasis on production readiness, scalability, and rigorous methodology.