Sr Machine Learning Engineer

About the Role

Uber’s Core Security Engineering org is re‑imagining how identity is protected and managed by fusing large‑scale machine learning with modern agentic AI. As a Senior Machine Learning Engineer you’ll lead two complementary tracks: building context‑aware authentication models that decide when and how to challenge users, and creating an agentic AI workflow engine that automates IAM operations—think an LLM‑powered copilot that files, executes, and verifies tasks such as user provisioning, access reviews, and policy changes. No prior security background is required; what matters is your ability to ship reliable, production‑grade ML systems.

What You’ll Do

• Risk‑based authentication – Design and deploy models that fuse behavioral biometrics, device posture, and network context to produce dynamic risk scores and trigger step‑up factors or session revocation in real time.
• Agentic AI workflow engine – Architect an LLM‑driven orchestration platform that can observe IAM events, plan multi‑step remediation or provisioning flows, and take safe actions across systems such as Okta, Active Directory, Duo, and ServiceNow.
• Productionize models and agents in high‑scale, low‑latency environments handling millions of auths and thousands of automated tickets per day.
• Build continuous feedback loops so both models and agents learn from outcomes and human approvals.
• Collaborate closely with IAM, SSO, infra, and detection teams to integrate your solutions end‑to‑end—from real‑time decisioning to post‑incident forensics.
• Lead design reviews, mentor engineers, and evangelize ML/GenAI best practices across the security and infrastructure orgs.

Minimum Qualifications

• 5+ years building ML or applied data‑science solutions, hands‑on experience with generative‑AI or agentic systems.
• Expert in Python, with proficiency in Go or Java; deep familiarity with ML/LLM frameworks such as PyTorch, TensorFlow, JAX, or LangChain.
• Demonstrated success running ML services in production at large scale and low latency.
• Strong communication and leadership skills; proven ability to set technical vision and influence roadmaps.

Preferred Qualifications

• Experience with reinforcement learning, retrieval‑augmented generation, or structured tool‑use frameworks for AI agents.
• Hands‑on work with risk scoring, anomaly detection, or fraud prevention pipelines.
• Familiarity with identity systems (Okta, Entra ID/AAD, SSO, MFA) or enterprise workflow tools (ServiceNow, Airflow) is a plus—but not required.
• Publications, open‑source contributions, or patents in ML, GenAI, or security automation.

Uber is proud to be an Equal Opportunity/Affirmative Action employer. All qualified applicants will receive consideration for employment without regard to sex, gender identity, sexual orientation, race, color, religion, national origin, disability, protected Veteran status, age, or any other characteristic protected by law. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. If you have a disability or special need that requires accommodation, please let us know by completing this form.

Offices continue to be central to collaboration and Uber’s cultural identity. Unless formally approved to work fully remotely, Uber expects employees to spend at least half of their work time in their assigned office. For certain roles, such as those based at green-light hubs, employees are expected to be in-office for 100% of their time. Please speak with your recruiter to better understand in-office expectations for this role.

For San Francisco, CA-based roles: The base salary range for this role is USD$198,000 per year - USD$220,000 per year.

For Sunnyvale, CA-based roles: The base salary range for this role is USD$198,000 per year - USD$220,000 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. You will also be eligible for various benefits. More details can be found at the following link https://www.uber.com/careers/benefits.

Uber is proud to be an Equal Opportunity employer. All qualified applicants will receive consideration for employment without regard to sex, gender identity, sexual orientation, race, color, religion, national origin, disability, protected Veteran status, age, or any other characteristic protected by law. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. If you have a disability or special need that requires accommodation, please let us know by completing this form.

Offices continue to be central to collaboration and Uber’s cultural identity. Unless formally approved to work fully remotely, Uber expects employees to spend at least half of their work time in their assigned office. For certain roles, such as those based at green-light hubs, employees are expected to be in-office for 100% of their time. Please speak with your recruiter to better understand in-office expectations for this role.