Staff Machine Learning Engineer - Risk and Trust

Uber’s Risk and Trust engineering organization is seeking a Staff Machine Learning Engineer to lead scalable machine learning initiatives focused on fraud prevention, identity verification, and account security. This role provides technical leadership across the end-to-end ML lifecycle and works closely with product, data science, and engineering partners to deliver measurable outcomes.

Role Responsibilities

• Partner with product, data science, and engineering teams to identify high-impact business opportunities, define complex machine learning problems, and contribute to the team’s technical roadmap.
• Use expertise in machine learning, optimization, and statistics to design and build innovative, scalable, and reliable ML solutions with measurable business impact.
• Lead technical execution for complex ML efforts, establish engineering best practices, and mentor other machine learning engineers to strengthen team capability.
• Own end-to-end development across data preparation, feature engineering, model development, system design, implementation, A/B testing, deployment, and production monitoring.

Required Qualifications

• 8+ years of industry experience developing machine learning models, including classical ML and deep learning, and deploying ML solutions into production.
• Master’s degree in Computer Science, Engineering, Mathematics, Statistics, or a related technical field.
• Strong problem-solving skills with a foundation in machine learning algorithms, statistics, and optimization.
• Proven ability to apply ML techniques to complex, large-scale, real-world problems.
• Proficiency in Python and experience using 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.

Preferred Qualifications

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

Tools and Technologies

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

Compensation and Benefits

• Base salary range: USD $232,000 - $258,000 per year for San Francisco, CA-based roles.
• 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.

Work Location and Office Expectations

Location: San Francisco, CA (onsite).

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