Data Scientist, ML Infrastructure

Salary: $114,297 - 235,319 per year Requirements:

• Were looking for at least 2 years of hands-on experience as an applied scientist, ML engineer, research scientist, or software engineer, with substantial production ML exposure.
• We need strong Python proficiency, plus experience with PyTorch or a comparable deep learning framework.
• Familiarity with distributed computing tools such as Spark or Ray is important; Ray experience is especially valued.
• We want someone enthusiastic about building tools and platforms that scale impact across an entire ML organization, not just solving isolated problems.
• You should have deep ML theory knowledge and strong first-principles reasoning about models.
• We expect solid software development practices, including version control, code review, and reproducible ML pipelines.
• Experience with workflow orchestration tools such as Airflow, Prefect, Jenkins, or similar is required.
• A bachelors or masters degree in a relevant area such as Computer Science, or equivalent practical experience, is needed.

• We will have you translate research-grade data science workflows such as proxy metrics and staleness models into production ML pipelines using Airflow, WandB, and Ray.
• You will apply and operationalize causal inference methods, including propensity scoring, IPW, and TMLE, to answer high-stakes measurement questions beyond experimentation limits.
• You will build self-serve tooling that enables non-experts to generate rigorous causal insights at scale.
• Well rely on you to partner with ML engineers and product teams to uncover opportunities for better tooling, stronger metrics, and improved measurement methods.
• You will use our metadata and engagement signals to create data-driven frameworks, from feature importance to content deindexing, that improve platform efficiency and speed.
• You will design and develop centralized ML platform tooling that strengthens feature and model creation, evaluation, trust, and daily production operation across our models.
• We expect you to establish reusable patterns and methodological standards that other teams can adopt.
• You will drive end-to-end design of production ML systems and help convert successful research into durable platform capabilities.

• AI
• Airflow
• Jenkins
• PyTorch
• Python
• Spark
• DevOps
• Support

More:

We are Pinterest, a platform where millions of people discover creative ideas, imagine new possibilities, and plan meaningful moments. Were building a career environment that values innovation, growth, diverse experiences, and flexibility so people can do their best work. AI plays a central role in our product and our hiring process, and were looking for people excited to collaborate with it. This is a remote-eligible U.S. role focused on advancing ML measurement, feature understanding, and causal inference at scale. The position is not eligible for relocation assistance, requires in-office collaboration 3–5 times per quarter, and can be based anywhere in the country. The role is also eligible for equity, with a base salary range of $114,297 to $235,319 USD, and we are committed to an equitable, inclusive, and inspiring workplace.

last updated 33 week of 2026