Staff ML Engineer, Risk & Trust - End-to-End ML Leader

Uber; San Francisco (CA); On-site; USD 232,000 - 258,000; Full time

Benefits offered by this job

Bonus program

Equity award

401(k)

Various benefits

Job summary

Uber is seeking a Staff Machine Learning Engineer to own end-to-end ML lifecycle for fraud, identity verification, and account security solutions. You will drive technical leadership, partner with product and data science teams, and deliver measurable business impact from scalable ML models.

Location is San Francisco, onsite, with compensation between USD 232,000 and 258,000 per year. Strong background in Python, PyTorch, TensorFlow, or JAX is required along with Spark/SQL experience.

Qualifications

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

Responsibilities

• Collaborate with product, data science, and engineering partners to identify high-impact ML opportunities and shape roadmaps.
• Apply ML techniques to deliver scalable, robust solutions tied to business outcomes.
• Provide technical leadership and mentor engineers to strengthen ML capabilities.
• Own end-to-end ML lifecycle: data prep, feature engineering, model development, deployment, and monitoring.

Skills

ML problem solving

Production ML deployment

End-to-end ML lifecycle

Leadership

Education

Master’s degree (CS/Engineering/Math/Stats)

PhD (preferred)

Tools

Python

PyTorch

TensorFlow

JAX

Spark

SQL

Job description

Uber is seeking a Staff Machine Learning Engineer to own end-to-end ML lifecycle for fraud, identity verification, and account security solutions. You will drive technical leadership, partner with product and data science teams, and deliver measurable business impact from scalable ML models.

Location is San Francisco, onsite, with compensation between USD 232,000 and 258,000 per year. Strong background in Python, PyTorch, TensorFlow, or JAX is required along with Spark/SQL experience.