Director, Machine Learning Engineering, Programmatic Ads
Director, Machine Learning Engineering, Programmatic Ads
Job Description
Responsibilities
- Manage and grow the engineering team, providing technical vision and long-term roadmap
- Design and implement algorithms for real-time bidding, ad scoring/ranking, inventory selection and yield optimization on the DSP
- Hire, mentor and grow a team of engineers. Set technical direction, manage project roadmaps, and actively guide team execution. Collaborate across Product, Engineering, Marketing and Sales – translating business goals into ML requirements and ensuring solutions meet cross-functional needs
- Define and evangelize the ML roadmap for programmatic products. Present findings and roadmaps to senior leadership, and work with stakeholders to align analytics projects with company goals (e.g. privacy-first personalization, new DSP features)
Qualifications
- M.S/ PhD degree in Computer Science, Statistics or related field
- 10+ years of industry experience building production machine learning systems at scale, data mining, search, recommendations, and/or natural language processing
- Experience in programmatic advertising or information retrieval contexts (RTB, DSP/SSP, search). Familiarity with ad campaign metrics, auction mechanics and yield optimization
- Excellent at cross-functional collaboration and stakeholder communication
Locations
- San Francisco, CA, US; Palo Alto, CA, US; Seattle, WA, US; Los Angeles, CA, US
Salary
314,580 - 550,515 USD / yearly
Skills Required
- building production machine learning systems at scaleintermediate
- data miningintermediate
- searchintermediate
- recommendationsintermediate
- natural language processingintermediate
- programmatic advertisingintermediate
- information retrievalintermediate
- RTBintermediate
- DSP/SSPintermediate
- ad campaign metricsintermediate
- auction mechanicsintermediate
- yield optimizationintermediate
- cross-functional collaborationintermediate
- stakeholder communicationintermediate
Required Qualifications
- M.S/ PhD degree in Computer Science, Statistics or related field (experience)
- 10+ years of industry experience building production machine learning systems at scale, data mining, search, recommendations, and/or natural language processing (experience)
- Experience in programmatic advertising or information retrieval contexts (RTB, DSP/SSP, search). Familiarity with ad campaign metrics, auction mechanics and yield optimization (experience)
- Excellent at cross-functional collaboration and stakeholder communication (experience)
Responsibilities
- Manage and grow the engineering team, providing technical vision and long-term roadmap
- Design and implement algorithms for real-time bidding, ad scoring/ranking, inventory selection and yield optimization on the DSP
- Hire, mentor and grow a team of engineers. Set technical direction, manage project roadmaps, and actively guide team execution. Collaborate across Product, Engineering, Marketing and Sales – translating business goals into ML requirements and ensuring solutions meet cross-functional needs
- Define and evangelize the ML roadmap for programmatic products. Present findings and roadmaps to senior leadership, and work with stakeholders to align analytics projects with company goals (e.g. privacy-first personalization, new DSP features)
Tags & Categories
Director, Machine Learning Engineering, Programmatic Ads
Director, Machine Learning Engineering, Programmatic Ads
Job Description
Responsibilities
- Manage and grow the engineering team, providing technical vision and long-term roadmap
- Design and implement algorithms for real-time bidding, ad scoring/ranking, inventory selection and yield optimization on the DSP
- Hire, mentor and grow a team of engineers. Set technical direction, manage project roadmaps, and actively guide team execution. Collaborate across Product, Engineering, Marketing and Sales – translating business goals into ML requirements and ensuring solutions meet cross-functional needs
- Define and evangelize the ML roadmap for programmatic products. Present findings and roadmaps to senior leadership, and work with stakeholders to align analytics projects with company goals (e.g. privacy-first personalization, new DSP features)
Qualifications
- M.S/ PhD degree in Computer Science, Statistics or related field
- 10+ years of industry experience building production machine learning systems at scale, data mining, search, recommendations, and/or natural language processing
- Experience in programmatic advertising or information retrieval contexts (RTB, DSP/SSP, search). Familiarity with ad campaign metrics, auction mechanics and yield optimization
- Excellent at cross-functional collaboration and stakeholder communication
Locations
- San Francisco, CA, US; Palo Alto, CA, US; Seattle, WA, US; Los Angeles, CA, US
Salary
314,580 - 550,515 USD / yearly
Skills Required
- building production machine learning systems at scaleintermediate
- data miningintermediate
- searchintermediate
- recommendationsintermediate
- natural language processingintermediate
- programmatic advertisingintermediate
- information retrievalintermediate
- RTBintermediate
- DSP/SSPintermediate
- ad campaign metricsintermediate
- auction mechanicsintermediate
- yield optimizationintermediate
- cross-functional collaborationintermediate
- stakeholder communicationintermediate
Required Qualifications
- M.S/ PhD degree in Computer Science, Statistics or related field (experience)
- 10+ years of industry experience building production machine learning systems at scale, data mining, search, recommendations, and/or natural language processing (experience)
- Experience in programmatic advertising or information retrieval contexts (RTB, DSP/SSP, search). Familiarity with ad campaign metrics, auction mechanics and yield optimization (experience)
- Excellent at cross-functional collaboration and stakeholder communication (experience)
Responsibilities
- Manage and grow the engineering team, providing technical vision and long-term roadmap
- Design and implement algorithms for real-time bidding, ad scoring/ranking, inventory selection and yield optimization on the DSP
- Hire, mentor and grow a team of engineers. Set technical direction, manage project roadmaps, and actively guide team execution. Collaborate across Product, Engineering, Marketing and Sales – translating business goals into ML requirements and ensuring solutions meet cross-functional needs
- Define and evangelize the ML roadmap for programmatic products. Present findings and roadmaps to senior leadership, and work with stakeholders to align analytics projects with company goals (e.g. privacy-first personalization, new DSP features)
Tags & Categories