What You will do:
- Lead the design, development, optimization, and productionization of machine learning (ML) solutions for complex and high-impact problems.
- Build ML solutions to improve Uber’s marketplace efficiency while ensuring seamless, high-quality user experiences in real-world applications.
- Review code and designs of teammates, providing constructive feedback.
- Lead cross-functional collaborations across product, engineering, and science teams to drive system development from ideation to production.
Basic Qualifications:
- PhD or equivalent experience in Computer Science, Engineering, Mathematics or related field
- 5+ years of industry experience as an Applied Scientist/Machine Learning Engineer.
- Experience in exploratory data analysis, statistical modeling, hypothesis testing, and experimental design.
- Experience working with cross-functional teams(product, science, product ops etc).
- Proficiency in one or more object-oriented programming languages (e.g. Python, Go, Java, C++).
Preferred Qualification:
- Experience building algorithms with large scale data
- 7+ years of industry experience in machine learning, including building and deploying ML models.
- Experience working on large scale Machine Learning platforms
- Experience in modern deep learning architectures and probabilistic modeling.
- Expertise in the design and architecture of ML systems and workflows.
- Experience with optimization techniques, including reinforcement learning (RL), Bayesian methods, multi-armed bandits or other large scale global optimization techniques.
For New York, NY-based roles: The base salary range for this role is USD$223,000 per year - USD$248,000 per year.
For San Francisco, CA-based roles: The base salary range for this role is USD$223,000 per year - USD$248,000 per year.
For Seattle, WA-based roles: The base salary range for this role is USD$223,000 per year - USD$248,000 per year.
For Sunnyvale, CA-based roles: The base salary range for this role is USD$223,000 per year - USD$248,000 per year.