Jobs via Dice
Machine Learning Engineer II - Engagement Optimization
Jobs via Dice, San Francisco, California, United States, 94199
About The Role
Machine Learning Engineer II - Engagement Optimization
role at
Jobs via Dice Uber has evolved from a simple ride-hailing service to a comprehensive platform that connects users with various on-demand services in their cities. The Uber One Membership team is dedicated to enhancing the user experience by providing a convenient and engaging platform that caters to all their needs. Uber One Members enjoy exclusive benefits, including the best price, selection, priority, and perks, all in one place. With a growing membership base of over 30 million and expanding, Uber One has the potential to redefine the global membership landscape. Join us in shaping the future of Uber! What You Will Do
Design and build Machine Learning models responsible for large-scale applied machine learning in optimization and personalization. Build high throughput systems that process millions of datapoints each minute and serve hundreds of thousands of QPS. Collaborate with Product, Science and cross-functional teams to brainstorm new opportunities and solutions for model and product iteration. Write high-quality code and uphold standards for testing and coverage. Align with the team on solutions to ambiguous problems and analyze the tradeoffs of different technical solutions. Contribute to engineering cultivation in terms of quality, monitoring, and on-call practices. Basic Qualifications
Bachelor's degree or equivalent in Computer Science, Engineering, Mathematics or related field, with 2+ years of full-time engineering experience. Experience with big-data architecture, ETL frameworks, SQL and database systems such as Hive, Kafka, Cassandra, etc. 1+ years of experience in the development, training, productionization and monitoring of ML optimization solutions at scale. Experience working with multiple multi-functional teams (product, science, product ops etc.). Expertise in one or more object-oriented programming languages (e.g. Python, Go, Java, C++). Proven track records of being a fast learner and go-getter, with willingness to get out of the comfort zone. Preferred Qualifications
Experience with taking on vague business problems, translating them into ML + Optimization formulation, identifying the right features, model structure and optimization constraints, and delivering business impact. Experience with the design and architecture of ML systems and workflows. Experience in modern deep learning architectures, probabilistic models and causal inference/personalization/ranking. Experience in optimization (RL / Bayes / Bandits) and online learning. Experience with optimizing Spark queries for better CPU and memory efficiency. Experience owning and delivering a technically challenging, multi-quarter project end to end. Compensation and Location
For San Francisco, CA-based roles: The base salary range for this role is USD$167,000 per year - USD$185,500 per year. For Sunnyvale, CA-based roles: The base salary range for this role is USD$167,000 per year - USD$185,500 per year. For all US locations, you will be eligible to participate in Uber's bonus program, and may be offered an equity award & other types of comp. You will also be eligible for various benefits. More details can be found at the following link. Equal Opportunity
Uber's mission is to reimagine the way the world moves for the better. Uber is proud to be an Equal Opportunity employer. All qualified applicants will receive consideration for employment without regard to sex, gender identity, sexual orientation, race, color, religion, national origin, disability, protected Veteran status, age, or any other characteristic protected by law. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. If you have a disability or special need that requires accommodation, please let us know by completing this form.
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Machine Learning Engineer II - Engagement Optimization
role at
Jobs via Dice Uber has evolved from a simple ride-hailing service to a comprehensive platform that connects users with various on-demand services in their cities. The Uber One Membership team is dedicated to enhancing the user experience by providing a convenient and engaging platform that caters to all their needs. Uber One Members enjoy exclusive benefits, including the best price, selection, priority, and perks, all in one place. With a growing membership base of over 30 million and expanding, Uber One has the potential to redefine the global membership landscape. Join us in shaping the future of Uber! What You Will Do
Design and build Machine Learning models responsible for large-scale applied machine learning in optimization and personalization. Build high throughput systems that process millions of datapoints each minute and serve hundreds of thousands of QPS. Collaborate with Product, Science and cross-functional teams to brainstorm new opportunities and solutions for model and product iteration. Write high-quality code and uphold standards for testing and coverage. Align with the team on solutions to ambiguous problems and analyze the tradeoffs of different technical solutions. Contribute to engineering cultivation in terms of quality, monitoring, and on-call practices. Basic Qualifications
Bachelor's degree or equivalent in Computer Science, Engineering, Mathematics or related field, with 2+ years of full-time engineering experience. Experience with big-data architecture, ETL frameworks, SQL and database systems such as Hive, Kafka, Cassandra, etc. 1+ years of experience in the development, training, productionization and monitoring of ML optimization solutions at scale. Experience working with multiple multi-functional teams (product, science, product ops etc.). Expertise in one or more object-oriented programming languages (e.g. Python, Go, Java, C++). Proven track records of being a fast learner and go-getter, with willingness to get out of the comfort zone. Preferred Qualifications
Experience with taking on vague business problems, translating them into ML + Optimization formulation, identifying the right features, model structure and optimization constraints, and delivering business impact. Experience with the design and architecture of ML systems and workflows. Experience in modern deep learning architectures, probabilistic models and causal inference/personalization/ranking. Experience in optimization (RL / Bayes / Bandits) and online learning. Experience with optimizing Spark queries for better CPU and memory efficiency. Experience owning and delivering a technically challenging, multi-quarter project end to end. Compensation and Location
For San Francisco, CA-based roles: The base salary range for this role is USD$167,000 per year - USD$185,500 per year. For Sunnyvale, CA-based roles: The base salary range for this role is USD$167,000 per year - USD$185,500 per year. For all US locations, you will be eligible to participate in Uber's bonus program, and may be offered an equity award & other types of comp. You will also be eligible for various benefits. More details can be found at the following link. Equal Opportunity
Uber's mission is to reimagine the way the world moves for the better. Uber is proud to be an Equal Opportunity employer. All qualified applicants will receive consideration for employment without regard to sex, gender identity, sexual orientation, race, color, religion, national origin, disability, protected Veteran status, age, or any other characteristic protected by law. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. If you have a disability or special need that requires accommodation, please let us know by completing this form.
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