Senior Software Engineer - Machine Learning / Optimization
San Francisco, California
Employer: Uber
Industry: Engineering
Salary: $185000 per year
Job type: Full-Time
About the Role
Are you a passionate Machine Learning Engineer who thrives in fast-paced environments and enjoys building impactful solutions that shape the future of transportation?
Join our Driver Pricing team at Uber and be at the forefront of developing machine learning models that optimize driver earnings and overall platform efficiency. You will play a crucial role in designing, building, and deploying cutting-edge algorithms that determine fair and dynamic pricing for Uber drivers across the globe.
What the Candidate Will Need / Bonus Points
\\-\\-\\-\\- What the Candidate Will Do ----
- Design and build end-to-end machine learning pipelines
- Develop innovative pricing models
- Collaborate with cross-functional teams
\\-\\-\\-\\- Basic Qualifications ----
- Master's or Ph.D. in Computer Science, Statistics, or a related field.
- Minimum 5 years of experience in industry with a strong focus on machine learning and optimization.
- Proven experience in designing, building, and deploying machine learning models at scale.
- Strong understanding of statistical analysis and feature engineering techniques.
- Excellent communication and collaboration skills.
- Ability to work independently and take ownership of projects.
- Empathy for users; passion for transportation and the impact of technology on the industry.
\\-\\-\\-\\- Preferred Qualifications ----
- Experience with deep learning and transformers techniques.
- Experience building or initiating data-driven / optimization-driven products
- Experience working in a fast-paced, agile environment.
For San Francisco, CA-based roles: The base salary range for this role is USD$185,000 per year - USD$205,500 per year.
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 [https://www.uber.com/careers/benefits](https://www.uber.com/careers/benefits).
Uber is proud to be an Equal Opportunity/Affirmative Action 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](https://forms.gle/aDWTk9k6xtMU25Y5A).
Offices continue to be central to collaboration and Uber's cultural identity. Unless formally approved to work fully remotely, Uber expects employees to spend at least half of their work time in their assigned office. For certain roles, such as those based at green-light hubs, employees are expected to be in-office for 100% of their time. Please speak with your recruiter to better understand in-office expectations for this role.
Are you a passionate Machine Learning Engineer who thrives in fast-paced environments and enjoys building impactful solutions that shape the future of transportation?
Join our Driver Pricing team at Uber and be at the forefront of developing machine learning models that optimize driver earnings and overall platform efficiency. You will play a crucial role in designing, building, and deploying cutting-edge algorithms that determine fair and dynamic pricing for Uber drivers across the globe.
What the Candidate Will Need / Bonus Points
\\-\\-\\-\\- What the Candidate Will Do ----
- Design and build end-to-end machine learning pipelines
- Develop innovative pricing models
- Collaborate with cross-functional teams
\\-\\-\\-\\- Basic Qualifications ----
- Master's or Ph.D. in Computer Science, Statistics, or a related field.
- Minimum 5 years of experience in industry with a strong focus on machine learning and optimization.
- Proven experience in designing, building, and deploying machine learning models at scale.
- Strong understanding of statistical analysis and feature engineering techniques.
- Excellent communication and collaboration skills.
- Ability to work independently and take ownership of projects.
- Empathy for users; passion for transportation and the impact of technology on the industry.
\\-\\-\\-\\- Preferred Qualifications ----
- Experience with deep learning and transformers techniques.
- Experience building or initiating data-driven / optimization-driven products
- Experience working in a fast-paced, agile environment.
For San Francisco, CA-based roles: The base salary range for this role is USD$185,000 per year - USD$205,500 per year.
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 [https://www.uber.com/careers/benefits](https://www.uber.com/careers/benefits).
Uber is proud to be an Equal Opportunity/Affirmative Action 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](https://forms.gle/aDWTk9k6xtMU25Y5A).
Offices continue to be central to collaboration and Uber's cultural identity. Unless formally approved to work fully remotely, Uber expects employees to spend at least half of their work time in their assigned office. For certain roles, such as those based at green-light hubs, employees are expected to be in-office for 100% of their time. Please speak with your recruiter to better understand in-office expectations for this role.
Created: 2024-10-02
Reference: 130789
Country: United States
State: California
City: San Francisco
ZIP: 94130
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