Machine Learning Engineer, tvScientificPinterest • San Francisco, California, United States
Machine Learning Engineer, tvScientific
Pinterest
- San Francisco, California, United States
- San Francisco, California, United States
Über
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.
Discover a career where you ignite innovation for millions, transform passion into growth opportunities, celebrate each other's unique experiences and embrace theflexibility to do your best work. Creating a career you love? It's Possible.
At Pinterest, AI isn't just a feature, it's a powerful partner that augments our creativity and amplifies our impact, and we're looking for candidates who are excited to be a part of that. To get a complete picture of your experience and abilities, we'll explore your foundational skills and how you collaborate with AI.
Through our interview process, what matters most is that you can always explain your approach, showing us not just what you know, but how you think. You can read more about our AI interview philosophy and how we use AI in our recruiting process here. 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. Our platform is built by industry leaders with a long history in programmatic advertising, digital media, and ad verification who have now purpose-built a CTV performance platform advertisers can trust to grow their business.
We are seeking a Machine Learning Engineer to build out our simulation and AI capabilities. You'll design and implement systems that model the CTV advertising ecosystem - auction dynamics, bidding strategies, campaign outcomes, and counterfactual scenarios - and develop AI-driven tools that accelerate how we build, test, and deploy ML systems.
What you'll do:
Design and build simulation environments that model CTV auction mechanics, inventory supply, and advertiser competition
Develop counterfactual and what-if frameworks for evaluating bidding strategies, budget allocation, and pacing algorithms offline
Build AI agents that explore strategy spaces, generate hypotheses, and automate experimentation within simulated environments
Use LLMs and generative AI to accelerate internal ML workflows - synthetic data generation, code generation, automated analysis, and rapid prototyping
Use simulation to de-risk ML model deployments - validate new bidding and optimization strategies before they touch live traffic
Define the technical direction for simulation and AI infrastructure and mentor engineers on the team
What we're looking for:
Strong production Python skills and experience building simulation or modeling systems
Deep understanding of probabilistic modeling, stochastic processes, or agent-based simulation
Hands-on experience with modern AI tools: LLMs, code generation, agentic workflows - and good judgment about when they help vs. when they don't
Adtech experience: you understand auction theory, RTB mechanics, and the dynamics of programmatic advertising
Ability to translate business questions ("what happens if we change our bid strategy?") into rigorous simulation frameworks
Clear written communication: you'll be defining new technical directions and need to bring others along
Ownership: you scope, design, and ship systems end-to-end with minimal direction
Nice-to-Haves:
Causal inference - uplift modeling, synthetic controls, difference-in-differences, or incrementality testing
Experience with discrete event simulation, Monte Carlo methods, or digital twins
Reinforcement learning - using simulated environments for policy learning and evaluation
Experience building agentic AI systems or multi-agent simulations
Big data experience with Scala and Spark
Systems programming experience in Zig or similar (C, C++, Rust)
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.
#LI-SM4
#LI-REMOTE At Pinterest we believe the workplace should be equitable, inclusive, and inspiring for every employee. In an effort to provide greater transparency, we are sharing the base salary range for this position. The position is also eligible for equity. Final salary is based on a number of factors including location, travel, relevant prior experience, or particular skills and expertise.
Information regarding the culture at Pinterest and benefits available for this position can be found here. US based applicants only
$123,696—$254,667 USD
Our Commitment to Inclusion:
Pinterest is an equal opportunity employer and makes employment decisions on the basis of merit. We want to have the best qualified people in every job. 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 completethis formfor support.
Sprachkenntnisse
- English
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