Machine Learning Scientist 5 - Ads Bidding in New York at Jobgether

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Machine Learning Scientist 5 - Ads Bidding based in United States.

This role offers the opportunity to shape machine learning systems at the intersection of advertising, optimization, and large-scale personalization.
You will design intelligent bidding algorithms that improve advertiser outcomes while supporting a high-quality member experience.
The position combines advanced ML research with hands-on production deployment using large-scale real-world data.
You’ll tackle complex challenges involving marketplace dynamics, seasonality, distribution shifts, and optimization.
Working closely with product and cross-functional teams, you’ll influence bidding objectives, auction design, and business strategy.
Your work will directly contribute to the evolution of a sophisticated, data-driven advertising ecosystem.
The environment values rigorous experimentation, strong technical judgment, collaboration, and measurable impact.

• 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.

• 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.

• 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.