Machine Learning Scientist 5 - Ads Bidding
Jobgether United States · $466K–$750K/yr
Internet Marketplace Platforms · 11-50 employees
About the role
Design and implement machine learning-driven bidding algorithms optimized for metrics like clicks, conversions, and ROAS. Collaborate with product teams to define bidding goals and translate technical findings into actionable business recommendations.
What they look for
Requirements
Requires an advanced degree such as a Master’s or PhD in a quantitative discipline and strong proficiency in Python, Scala, or Java. Candidates must have hands-on experience deploying machine learning algorithms in large-scale production environments, preferably within advertising or marketplace settings.
Benefits
Full description
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.
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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.
\nHow Jobgether works:
We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.
We appreciate your interest and wish you the best!
Why Apply Through Jobgether?
Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.
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