Machine Learning Scientist 5 - Ads Bidding

Accountabilities:

• • Design and implement machine learning-driven bidding algorithms optimized for objectives such as clicks, conversions, CPA, and ROAS.
  • Build, train, test, and deploy bidding algorithms using large-scale production datasets, ensuring they remain robust to changing marketplace conditions, seasonality, and distribution shifts.
  • Develop rigorous online and offline evaluation frameworks to measure the effectiveness of bidding algorithms, policy changes, and experiments.
  • Contribute to auction and pricing mechanism design, balancing algorithmic performance, marketplace efficiency, and broader business objectives.
  • Partner with product teams to define bidding goals, constraints, priorities, and trade-offs that support product and revenue outcomes.
  • Translate complex technical findings into clear recommendations, communicating decisions, trade-offs, and experiment results to both technical and non-technical stakeholders.
  • Help advance data-driven advertising capabilities by applying sophisticated modeling, optimization, and experimentation techniques to real-world problems.

  Requirements:

  • Advanced degree, such as a Master’s or PhD, in Computer Science, Statistics, Mathematics, or another quantitative discipline.
  • Strong proficiency in Python, Scala, Java, or comparable programming languages used for machine learning and large-scale data applications.
  • Deep knowledge of machine learning, optimization, statistical analysis, and data-driven modeling techniques.
  • Demonstrated experience prototyping and deploying algorithms using large-scale production data.
  • Hands-on experience designing or developing bidding algorithms, preferably within advertising, auctions, marketplaces, or other optimization-driven environments.
  • Strong understanding of how to evaluate ML systems and translate experimental or technical results into measurable business impact.
  • Strong business acumen, with the ability to connect technical solutions to product, revenue, and marketplace objectives.
  • Excellent written and verbal communication skills, with the ability to collaborate effectively across technical and product teams.
  • Ability to work through complex, ambiguous problems while balancing experimentation, technical rigor, and practical business considerations.

  Benefits:

  • Annual salary range of $466,000–$750,000, varying based on location and individual factors.
  • Compensation is structured around annual salary, with the flexibility to choose the balance between salary and stock options; the role does not include bonuses.
  • Comprehensive health plans, including medical and mental health support.
  • Dental and vision coverage.
  • 401(k) retirement plan with employer match.
  • Stock option program.
  • Health Savings Accounts and Flexible Spending Accounts.
  • Disability programs and life and serious injury benefits.
  • Family-forming benefits.
  • Paid leave programs and flexible time off for full-time salaried employees.
  • Remote work opportunity within the United States, with locations also listed in Los Angeles and Los Gatos.
  • An inclusive environment focused on collaboration, innovation, and meaningful technical impact.