Sr. Machine Learning Engineer, tvScientific

Pinterest; United States; Hybrid; USD 155,584 - 320,320; Full time

Job summary

Pinterest is seeking a skilled individual with strong production Python skills for a role that involves real-time bidding and ML model development. Candidates should have at least 4 years of industry experience and a Bachelor’s degree in a relevant field.

The position offers competitive compensation ranging from $155,584 to $320,320 USD. The role supports a hybrid working model with a commitment to inclusivity across diverse backgrounds.

Qualifications

• 4+ years of industry experience.
• Ability to build internal tools with LLMs and generative AI.
• Experience in MLOps such as model deployment and monitoring.

Responsibilities

• Write production Python that powers real-time bidding and campaign optimization.
• Train, deploy, and monitor ML models.
• Design and implement new ML products across the ad-buying lifecycle.

Skills

Production Python skills

Statistics and ML fundamentals

Familiarity with modern AI tools

AdTech or CTV experience

Clear written communication

Comfort with ambiguity

Education

Bachelor’s degree in Computer Science, Mathematics, Engineering, or related field

Tools

Cursor

Copilot

Spark

Job description

About Pinterest

Millions of people around the world come to our platform 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.

About tvScientific

tvScientific is the first and only CTV advertising platform purpose‑built for performance marketers. We leverage massive data and cutting‑edge science to automate and optimize TV advertising to drive business outcomes. Our solution combines media buying, optimization, measurement, and attribution in one efficient platform. We help advertisers buy ads across the CTV ecosystem—Hulu, Pluto TV, Disney+, HBO Max, and hundreds of FAST channels—and prove that those ads drove real business outcomes.

What You’ll Do

• Write production Python that powers real‑time bidding, model training, and campaign optimization.
• Train, deploy, and monitor ML models that decide which ads to show, when, and at what price—millions of bid decisions per second.
• Build and improve incrementality‑measurement systems, helping advertisers understand the true causal lift of their CTV spend.
• Design and implement new ML products across the ad‑buying lifecycle: audience targeting, bid optimization, pacing, and attribution.
• Use LLMs and generative AI to build internal tools that accelerate how we develop, test, and ship ML systems.
• Serve as a technical lead and mentor on a distributed engineering team.

What We’re Looking For

• Strong production Python skills: you write code that runs in prod, not just notebooks.
• Solid statistics and ML fundamentals: you can reason about experiment design, model evaluation, and when simpler approaches beat complex ones.
• Familiarity with modern AI tools and good judgment about where they add value.
• AdTech or CTV experience: familiarity with RTB, programmatic advertising, and supply‑path optimization.
• Clear written communication: we’re a distributed team and writing is how decisions get made.
• Comfort with ambiguity: you’ll own problems end‑to‑end in a fast‑moving environment, from scoping to shipping.
• Bachelor’s degree in Computer Science, Mathematics, Engineering, related field, or equivalent experience.
• 4+ years of industry experience.

Nice‑to‑Haves

• Experience using Cursor, Copilot, Codex, or similar AI coding assistants for development, debugging, testing, and refactoring.
• Familiarity with LLM‑powered productivity tools for documentation search, experiment analysis, SQL/data exploration, and engineering workflow acceleration.
• Causal inference: uplift modeling, synthetic controls, difference‑in‑differences, or incrementality testing.
• Big data experience with Scala and Spark.
• Systems programming experience in Zig or similar (C, C++, Rust).
• Reinforcement learning or bandit algorithms in production.
• Experience building agentic AI systems or LLM‑powered workflows.
• MLOps experience: model deployment, monitoring, and pipeline orchestration on AWS.

In‑Office Requirement Statement

We recognize that the ideal environment for work is situational and may differ across departments. What this looks like day‑to‑day can vary based on the needs of each organization or role.

Relocation Statement

This position is not eligible for relocation assistance. Visit our PinFlex page to learn more about our working model.

Compensation

US based applicants only. $155,584—$320,320 USD.

Our Commitment to Inclusion

Pinterest is an equal‑opportunity employer and makes employment decisions on the basis of merit. All qualified applicants will receive consideration for employment without regard to race, color, ancestry, national origin, religion or religious creed, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender, gender identity, gender expression, age, marital status, status as a protected veteran, physical or mental disability, medical condition, genetic information or characteristics (or those of a family member), or any other consideration made unlawful by applicable federal, state or local laws. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. If you require a medical or religious accommodation during the job application process, please complete this form for support.

Authorization Statement

By submitting this application, I certify that all information submitted in my application and throughout the hiring process is true, accurate, and complete to the best of my knowledge. I understand that any false statement, omission, or misrepresentation may disqualify me from employment consideration or result in termination if discovered after hire.