Staff Machine Learning Engineer, User Understanding
Staff Machine Learning Engineer, User Understanding
Job Description
Responsibilities
- Lead and mentor a team of experienced machine learning engineers in developing advanced user understanding models and systems, which are integral to key Pinterest products across Discovery, Ads, and Growth.
- Collaborate cross-functionally with partners in Product, Data Science, and Engineering to define strategy, set priorities, and effectively integrate user insights into core systems and product features.
- Drive experimentation and adoption of new user understanding models with product teams across Pinterest, ensuring measurable end-to-end impact on key metrics.
- Manage project execution and stakeholder communication, including roadmap planning, technical decision-making, risk mitigation, and progress updates to achieve business goals.
- Provide thought leadership in user modeling and recommender systems by setting a long-term technical vision and advancing the state-of-the-art in the field.
Qualifications
- Hands-on experience developing and deploying large-scale machine learning systems in search, recommendation or advertising.
- Demonstrated ML expertise with a proven track record of impactful solutions and a deep understanding of large scale distributed systems.
- 6+ years of industry experience in applied machine learning or closely related roles.
- Strong technical leadership, including a passion for driving technical direction, system architecture, and designing robust, scalable ML solutions.
- Bachelor’s/Master’s degree in a relevant field such as computer science or equivalent experience.
Locations
- San Francisco, CA, US; Remote, US (Remote)
Salary
189,308 - 389,753 USD / yearly
Estimated Salary Rangemedium confidence
220,000 - 350,000 USD / yearly
Source: ai estimated
* This is an estimated range based on market data and may vary based on experience and qualifications.
Skills Required
- developing and deploying large-scale machine learning systemsintermediate
- search systemsintermediate
- recommendation systemsintermediate
- advertising systemsintermediate
- ML expertiseintermediate
- large scale distributed systemsintermediate
- technical leadershipintermediate
- system architectureintermediate
- scalable ML solutionsintermediate
- user modelingintermediate
- recommender systemsintermediate
Required Qualifications
- Hands-on experience developing and deploying large-scale machine learning systems in search, recommendation or advertising. (experience)
- Demonstrated ML expertise with a proven track record of impactful solutions and a deep understanding of large scale distributed systems. (experience)
- 6+ years of industry experience in applied machine learning or closely related roles. (experience)
- Strong technical leadership, including a passion for driving technical direction, system architecture, and designing robust, scalable ML solutions. (experience)
- Bachelor’s/Master’s degree in a relevant field such as computer science or equivalent experience. (experience)
Responsibilities
- Lead and mentor a team of experienced machine learning engineers in developing advanced user understanding models and systems, which are integral to key Pinterest products across Discovery, Ads, and Growth.
- Collaborate cross-functionally with partners in Product, Data Science, and Engineering to define strategy, set priorities, and effectively integrate user insights into core systems and product features.
- Drive experimentation and adoption of new user understanding models with product teams across Pinterest, ensuring measurable end-to-end impact on key metrics.
- Manage project execution and stakeholder communication, including roadmap planning, technical decision-making, risk mitigation, and progress updates to achieve business goals.
- Provide thought leadership in user modeling and recommender systems by setting a long-term technical vision and advancing the state-of-the-art in the field.
Tags & Categories
Staff Machine Learning Engineer, User Understanding
Staff Machine Learning Engineer, User Understanding
Job Description
Responsibilities
- Lead and mentor a team of experienced machine learning engineers in developing advanced user understanding models and systems, which are integral to key Pinterest products across Discovery, Ads, and Growth.
- Collaborate cross-functionally with partners in Product, Data Science, and Engineering to define strategy, set priorities, and effectively integrate user insights into core systems and product features.
- Drive experimentation and adoption of new user understanding models with product teams across Pinterest, ensuring measurable end-to-end impact on key metrics.
- Manage project execution and stakeholder communication, including roadmap planning, technical decision-making, risk mitigation, and progress updates to achieve business goals.
- Provide thought leadership in user modeling and recommender systems by setting a long-term technical vision and advancing the state-of-the-art in the field.
Qualifications
- Hands-on experience developing and deploying large-scale machine learning systems in search, recommendation or advertising.
- Demonstrated ML expertise with a proven track record of impactful solutions and a deep understanding of large scale distributed systems.
- 6+ years of industry experience in applied machine learning or closely related roles.
- Strong technical leadership, including a passion for driving technical direction, system architecture, and designing robust, scalable ML solutions.
- Bachelor’s/Master’s degree in a relevant field such as computer science or equivalent experience.
Locations
- San Francisco, CA, US; Remote, US (Remote)
Salary
189,308 - 389,753 USD / yearly
Estimated Salary Rangemedium confidence
220,000 - 350,000 USD / yearly
Source: ai estimated
* This is an estimated range based on market data and may vary based on experience and qualifications.
Skills Required
- developing and deploying large-scale machine learning systemsintermediate
- search systemsintermediate
- recommendation systemsintermediate
- advertising systemsintermediate
- ML expertiseintermediate
- large scale distributed systemsintermediate
- technical leadershipintermediate
- system architectureintermediate
- scalable ML solutionsintermediate
- user modelingintermediate
- recommender systemsintermediate
Required Qualifications
- Hands-on experience developing and deploying large-scale machine learning systems in search, recommendation or advertising. (experience)
- Demonstrated ML expertise with a proven track record of impactful solutions and a deep understanding of large scale distributed systems. (experience)
- 6+ years of industry experience in applied machine learning or closely related roles. (experience)
- Strong technical leadership, including a passion for driving technical direction, system architecture, and designing robust, scalable ML solutions. (experience)
- Bachelor’s/Master’s degree in a relevant field such as computer science or equivalent experience. (experience)
Responsibilities
- Lead and mentor a team of experienced machine learning engineers in developing advanced user understanding models and systems, which are integral to key Pinterest products across Discovery, Ads, and Growth.
- Collaborate cross-functionally with partners in Product, Data Science, and Engineering to define strategy, set priorities, and effectively integrate user insights into core systems and product features.
- Drive experimentation and adoption of new user understanding models with product teams across Pinterest, ensuring measurable end-to-end impact on key metrics.
- Manage project execution and stakeholder communication, including roadmap planning, technical decision-making, risk mitigation, and progress updates to achieve business goals.
- Provide thought leadership in user modeling and recommender systems by setting a long-term technical vision and advancing the state-of-the-art in the field.
Tags & Categories