Leverage algorithmic knowledge in machine. learning/optimization/statistics to design robust engineering solutions to positively impact Uber's business.
Shape the MLE role and uplevel MLE talents in the org.
Be responsible for the End to End of the product - ML model pipeline & system design, implementation, AB testing, and rollout. Work with the team to productionize the solutions at scale.
Basic Qualifications
10+ years of industry experience developing machine learning models ( both classical and deep learning) and shipping ML solutions to production.
Master’s degree in Computer Science, Engineering, Mathematics or related field
Strong problem-solving skills, with expertise in ML methodologies
Experience in applying ML, statistics, or optimization techniques to solve large-scale real-world problems
Industry experience in ML frameworks (e.g. Tensorflow, Pytorch, or JAX) and complex data pipelines; programming languages such as Python, Spark SQL, Presto, Go, Java
Preferred Qualifications
PhD degree in Computer Science, Engineering, Mathematics or related field
Familiarity with multi-task learning, LLMs and anomaly detection
Fraud domain knowledge
For San Francisco, CA-based roles: The base salary range for this role is USD $267,000 per year - USD $297,000 per year.
For Seattle, WA-based roles: The base salary range for this role is USD $267,000 per year - USD $297,000 per year.
For Sunnyvale, CA-based roles: The base salary range for this role is USD $267,000 per year - USD $297,000 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. All full-time employees are eligible to participate in a 401(k) plan. You will also be eligible for various benefits.
