Distinguished Machine Learning Engineer, Monetization
Distinguished Machine Learning Engineer, Monetization
Job Description
Responsibilities
- Lead user-facing projects that involve end-to-end engineering development in both frontend and backend and ML
- Improve relevance and increase long term value for Pinners, Partners, Creators, and Pinterest through efficient Ads Delivery
- Improve our engineering systems to improve the latency, capacity, stability and reduce infra cost
- Collaborate with product managers and designers to develop engineering solutions for user-facing product improvements
- Collaborate with other engineering teams (infra, user modeling, content understanding) to leverage their platforms and signals
- Champion engineering excellence and a data driven culture, mentor senior tech talent and represent Pinterest externally in the tech and AI communities
Qualifications
- Degree in computer science, machine learning, statistics, or a related field
- 15+ years of working experience in engineering teams that build large-scale, ML-driven, user-facing products
- Experience leading cross-team engineering efforts that improve user experience in products
- Understanding of an object-oriented programming language such as Go, Java, C++, or Python
- Experience with large-scale data processing (e.g., Hive, Scalding, Spark, Hadoop, MapReduce)
- Strong software engineering and mathematical skills, with knowledge of statistical methods
- Experience working across frontend, backend, and ML systems for large-scale user-facing products, with a good understanding of how they all work together
- Hands-on experience with large-scale online e-commerce systems
- Excellent cross-functional collaboration and stakeholder communication skills, with strong execution in project management
Preferred Qualifications
- Background in computational advertising
Locations
- San Francisco, CA, US; Palo Alto, CA, US; Seattle, WA, US; New York, NY, US
Salary
347,264 - 607,712 USD / yearly
Skills Required
- Object-oriented programming (Go, Java, C++, Python)intermediate
- Large-scale data processing (Hive, Scalding, Spark, Hadoop, MapReduce)intermediate
- Software engineeringintermediate
- Mathematical skillsintermediate
- Statistical methodsintermediate
- Frontend systemsintermediate
- Backend systemsintermediate
- ML systemsintermediate
- Large-scale online e-commerce systemsintermediate
- Cross-functional collaborationintermediate
- Stakeholder communicationintermediate
- Project managementintermediate
Required Qualifications
- Degree in computer science, machine learning, statistics, or a related field (experience)
- 15+ years of working experience in engineering teams that build large-scale, ML-driven, user-facing products (experience)
- Experience leading cross-team engineering efforts that improve user experience in products (experience)
- Understanding of an object-oriented programming language such as Go, Java, C++, or Python (experience)
- Experience with large-scale data processing (e.g., Hive, Scalding, Spark, Hadoop, MapReduce) (experience)
- Strong software engineering and mathematical skills, with knowledge of statistical methods (experience)
- Experience working across frontend, backend, and ML systems for large-scale user-facing products, with a good understanding of how they all work together (experience)
- Hands-on experience with large-scale online e-commerce systems (experience)
- Excellent cross-functional collaboration and stakeholder communication skills, with strong execution in project management (experience)
Preferred Qualifications
- Background in computational advertising (experience)
Responsibilities
- Lead user-facing projects that involve end-to-end engineering development in both frontend and backend and ML
- Improve relevance and increase long term value for Pinners, Partners, Creators, and Pinterest through efficient Ads Delivery
- Improve our engineering systems to improve the latency, capacity, stability and reduce infra cost
- Collaborate with product managers and designers to develop engineering solutions for user-facing product improvements
- Collaborate with other engineering teams (infra, user modeling, content understanding) to leverage their platforms and signals
- Champion engineering excellence and a data driven culture, mentor senior tech talent and represent Pinterest externally in the tech and AI communities
Tags & Categories
Distinguished Machine Learning Engineer, Monetization
Distinguished Machine Learning Engineer, Monetization
Job Description
Responsibilities
- Lead user-facing projects that involve end-to-end engineering development in both frontend and backend and ML
- Improve relevance and increase long term value for Pinners, Partners, Creators, and Pinterest through efficient Ads Delivery
- Improve our engineering systems to improve the latency, capacity, stability and reduce infra cost
- Collaborate with product managers and designers to develop engineering solutions for user-facing product improvements
- Collaborate with other engineering teams (infra, user modeling, content understanding) to leverage their platforms and signals
- Champion engineering excellence and a data driven culture, mentor senior tech talent and represent Pinterest externally in the tech and AI communities
Qualifications
- Degree in computer science, machine learning, statistics, or a related field
- 15+ years of working experience in engineering teams that build large-scale, ML-driven, user-facing products
- Experience leading cross-team engineering efforts that improve user experience in products
- Understanding of an object-oriented programming language such as Go, Java, C++, or Python
- Experience with large-scale data processing (e.g., Hive, Scalding, Spark, Hadoop, MapReduce)
- Strong software engineering and mathematical skills, with knowledge of statistical methods
- Experience working across frontend, backend, and ML systems for large-scale user-facing products, with a good understanding of how they all work together
- Hands-on experience with large-scale online e-commerce systems
- Excellent cross-functional collaboration and stakeholder communication skills, with strong execution in project management
Preferred Qualifications
- Background in computational advertising
Locations
- San Francisco, CA, US; Palo Alto, CA, US; Seattle, WA, US; New York, NY, US
Salary
347,264 - 607,712 USD / yearly
Skills Required
- Object-oriented programming (Go, Java, C++, Python)intermediate
- Large-scale data processing (Hive, Scalding, Spark, Hadoop, MapReduce)intermediate
- Software engineeringintermediate
- Mathematical skillsintermediate
- Statistical methodsintermediate
- Frontend systemsintermediate
- Backend systemsintermediate
- ML systemsintermediate
- Large-scale online e-commerce systemsintermediate
- Cross-functional collaborationintermediate
- Stakeholder communicationintermediate
- Project managementintermediate
Required Qualifications
- Degree in computer science, machine learning, statistics, or a related field (experience)
- 15+ years of working experience in engineering teams that build large-scale, ML-driven, user-facing products (experience)
- Experience leading cross-team engineering efforts that improve user experience in products (experience)
- Understanding of an object-oriented programming language such as Go, Java, C++, or Python (experience)
- Experience with large-scale data processing (e.g., Hive, Scalding, Spark, Hadoop, MapReduce) (experience)
- Strong software engineering and mathematical skills, with knowledge of statistical methods (experience)
- Experience working across frontend, backend, and ML systems for large-scale user-facing products, with a good understanding of how they all work together (experience)
- Hands-on experience with large-scale online e-commerce systems (experience)
- Excellent cross-functional collaboration and stakeholder communication skills, with strong execution in project management (experience)
Preferred Qualifications
- Background in computational advertising (experience)
Responsibilities
- Lead user-facing projects that involve end-to-end engineering development in both frontend and backend and ML
- Improve relevance and increase long term value for Pinners, Partners, Creators, and Pinterest through efficient Ads Delivery
- Improve our engineering systems to improve the latency, capacity, stability and reduce infra cost
- Collaborate with product managers and designers to develop engineering solutions for user-facing product improvements
- Collaborate with other engineering teams (infra, user modeling, content understanding) to leverage their platforms and signals
- Champion engineering excellence and a data driven culture, mentor senior tech talent and represent Pinterest externally in the tech and AI communities
Tags & Categories