Staff Machine Learning Engineer - Risk and Trust

Uber’s Risk and Trust engineering organization builds machine learning systems that help protect users and the platform through scalable fraud detection, identity verification, and account security. As a Staff Machine Learning Engineer, you’ll lead development efforts end to end, from defining ML problems through deployment and ongoing monitoring, while collaborating closely across product, data science, and engineering.

This role is based in San Francisco, CA on an onsite schedule. The annual salary range is USD 232,000 - 258,000, and the position requires 8+ years of relevant experience.

What you’ll do

• Work with product, data science, and engineering partners to identify high-impact opportunities, formulate complex ML problems, and contribute to the team’s technical roadmap.
• Use deep expertise in machine learning, optimization, and statistics to design and build scalable, robust ML solutions with measurable business impact.
• Provide technical leadership across complex ML initiatives, promote engineering best practices, and mentor other machine learning engineers to raise team capability.
• Own the full ML development lifecycle, including data preparation, feature engineering, model development, system design, implementation, A/B testing, deployment, and production monitoring.

What you bring

• 8+ years of industry experience developing ML models, including classical ML and deep learning, and deploying ML solutions to production.
• Master’s degree in Computer Science, Engineering, Mathematics, Statistics, or a related technical field.
• Strong problem-solving skills and a solid foundation in machine learning algorithms, statistics, and optimization.
• Experience applying ML techniques to solve complex, large-scale real-world problems.
• Proficiency in Python and experience with modern ML frameworks such as PyTorch, TensorFlow, or JAX.
• Experience building large-scale data pipelines and working with distributed data processing frameworks such as Spark and SQL-based systems.

Technologies

• Python
• PyTorch
• TensorFlow
• JAX
• Spark
• SQL

Preferred qualifications

• PhD in Computer Science, Engineering, Mathematics, Statistics, or a related technical field.
• Hands-on experience with advanced ML techniques such as deep learning, representation learning, sequence modeling, multi-task learning, reinforcement learning, or large language models.
• Experience building ML solutions for fraud detection, anomaly detection, or other adversarial environments.
• Proven ability to drive complex ML projects independently from problem formulation through production deployment.
• Experience with large-scale, real-time ML systems and data-driven decision making in production environments.

Compensation and benefits

• Eligible to participate in Uber’s bonus program.
• May be offered an equity award and other types of compensation.
• Eligible to participate in a 401(k) plan.
• Eligible for various benefits.

Office requirements

• Unless approved for full remote work, employees must spend at least 50% of their time in-office.
• Some roles, including those at greenlight hubs, require full-time in-office presence.