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Machine Learning Engineer, tvScientific

직무머신러닝
경력미들급
위치San Francisco, Canada, United States
근무원격
고용정규직
게시2개월 전
지원하기

필수 스킬

Python

Machine Learning

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.

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 tv Scientific

tv Scientific 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 Pin Flex page to learn more about our working model.

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 complete this form for support.

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Pinterest 소개

Pinterest

Pinterest

Public

Pinterest is an American social media service for publishing and discovery of information in the form of digital pinboards. This includes recipes, home, style, motivation, and inspiration on the Internet using image sharing. Pinterest, Inc.

1,001-5,000

직원 수

San Francisco

본사 위치

$18.7B

기업 가치

리뷰

10개 리뷰

3.8

10개 리뷰

워라밸

3.8

보상

2.7

문화

4.1

커리어

2.5

경영진

3.0

65%

지인 추천률

장점

Flexible work arrangements and remote options

Great team culture and collaboration

Work-life balance

단점

Limited career advancement and growth opportunities

Below average salary compensation

Management responsiveness and direction issues

연봉 정보

63개 데이터

Junior/L3

Mid/L4

Senior/L5

Staff/L6

Junior/L3 · Machine Learning Engineer I

8개 리포트

$153,318

총 연봉

기본급

$148,699

주식

-

보너스

-

$153,318

$153,318

면접 후기

후기 3개

난이도

3.0

/ 5

소요 기간

14-28주

면접 과정

1

Application Review

2

Recruiter Screen

3

Technical Phone Screen

4

Onsite/Virtual Interviews

5

Team Matching

6

Offer

자주 나오는 질문

Coding/Algorithm

System Design

Behavioral/STAR

Technical Knowledge

Culture Fit