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Senior Machine Learning Engineer, Ads Optimization
Reddit
United States
Remote
Full-time
$217k - $303k
1d ago
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Responsibilities
Design and implement machine learning models and optimization policies to compute bids across varied performance objectives like CPC, CPA, and ROAS.
Develop smooth budget pacing algorithms across accounts, campaigns, and ad groups to prevent overspend and underspend.
Formulate complex marketplace goals into mathematical optimization problems with constraints covering revenue, delivery smoothness, and user experience.
Build and maintain scalable data processing pipelines and real-time inference systems supporting auction decision-making.
Lead multi-quarter technical initiatives for ads optimization and set technical direction for the bidding infrastructure.
Collaborate cross-functionally with Product, Data Science, and Infrastructure teams to design, test, and roll out marketplace improvements.
Mentor and guide other machine learning engineers on best practices, system design, and optimization techniques.
Qualifications
At least 3 to 5 years of production machine learning experience, with 5 or more years preferred for senior IC4-level execution.
Strong software engineering proficiency in programming languages such as Python, Java, or Go.
Proven background in designing and operating scalable data processing architectures using tools like Spark, Kafka, Airflow, BigQuery, or Redis.
Strong background in quantitative optimization and applied mathematics, with the ability to implement custom optimization algorithms rather than solely relying on off-the-shelf tooling.
Demonstrated track record of translating complex, ambiguous business problems into measurable production metrics.
Direct experience in digital advertising, auction theory, mechanism design, pacing algorithms, or large-scale online marketplaces.
Familiarity with real-time decisioning systems and low-latency production serving infrastructure.
Advanced degree (Master's or PhD) in Computer Science, Operations Research, Applied Mathematics, Economics, or a related quantitative discipline.
Work Environment
Full-time remote work arrangement available across the United States.
Tight-knit, highly collaborative engineering culture working alongside cross-functional partners in Product and Data Science.
Standard 40-hour work week operating within typical US business time zones.
Benefits & Perks
Annual base salary range between $216,700 and $303,400 USD alongside equity grants in the form of Restricted Stock Units (RSUs).
Comprehensive medical, dental, and vision insurance with income replacement programs, family planning, and gender-affirming care.
401(k) retirement plan featuring an employer match program.
Flexible vacation policy, paid volunteer time off, and generous paid parental leave.
Dedicated budgets and programs for remote workspace support, professional coaching, and ongoing career development.