Risk And Trust Engineer Jobs

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Staff Machine Learning Engineer - Risk and Trust

Uber San Francisco, CA

San Francisco, CA

Today

$232k - $258k/yr Full time Ai Ml Artificial Intelligence Data Analytics

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Job Description

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.

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