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Senior Machine Learning Engineer

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Senior Machine Learning Engineer in USA

  • Remote

Responsibilities

  • Design and implement models and policies for CPC, CPA, and ROAS-based bidding objectives.
  • Develop pacing systems that distribute campaign budgets smoothly while preventing overspend and underspend.
  • Allocate spend and auction participation across segments, surfaces, and time zones.
  • Translate marketplace and product goals into optimization problems and constraints involving ROI, revenue, delivery smoothness, fairness, and user experience.
  • Own systems from problem formulation and algorithm design through experimentation, production deployment, and ongoing iteration.
  • Lead complex or multi-quarter initiatives, set technical direction, and mentor other engineers while remaining hands-on.

Requirements

  • Have 3–5+ years of experience building, deploying, and operating machine learning systems in production; IC4 candidates typically have 5+ years.
  • Demonstrate strong programming skills in Python, Java, Go, or similar languages and solid software engineering fundamentals.
  • Have experience designing scalable data processing systems such as those using Spark, Kafka, Airflow, BigQuery, or Redis.
  • Translate ambiguous product or business problems into measurable solutions.
  • Demonstrate strong mathematics and optimization skills, with a degree or equivalent background in a quantitative field such as mathematics, physics, quantitative finance, economics, or operations research, or experience in optimization-heavy domains.
  • Implement custom optimization logic, including gradient-based methods and constraint handling, rather than relying solely on black-box tools.
  • Preferred qualifications include experience with advertising or auction systems, online marketplaces, search or ranking systems, bidding, pacing, budget optimization, auction or mechanism design, and campaign performance optimization.
  • Preferred qualifications include familiarity with large-scale real-time, low-latency decision systems; feature engineering; model optimization; production ML monitoring; cross-functional Ads or marketplace collaboration; and project leadership through rollout.
  • An advanced degree in Computer Science, Machine Learning, Operations Research, Applied Math, or a related quantitative field is preferred.

Benefits

  • Comprehensive healthcare benefits and income replacement programs.
  • 401(k) with employer match.
  • Global benefits supporting workspace, professional development, caregiving, and lifestyle needs.
  • Family planning support and gender-affirming care.
  • Mental health and coaching benefits.
  • Flexible vacation and paid volunteer time off.
  • Generous paid parental leave.
  • The role is a US-based position with a stated base salary range of $216,700–$303,400 USD, plus potential equity and, depending on the position, commission.
  • Interviews may be recorded, transcribed, and summarized by artificial intelligence, with an option to opt out before scheduled interviews.

Salary: $217k - $303k/yr

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