Sr Machine Learning Engineer

• Experience training deep feed-forward models (MLP) for uplift estimation.
• Experience with constrained optimization applied to resource allocation (LP/MIP, Lagrangian duality, dual-price or bidding-style budget pacing).
• Experience with incentive, promotion, pricing, or discount targeting at consumer scale.
• Experience with contextual bandits or reinforcement learning for sequential decisioning.
• Familiarity with subscription businesses: trial-to-paid conversion, retention curves, LTV modeling, cannibalization, and incrementality measurement.
• Experience leading technical direction across an ambiguous, cross-functional scope.

For San Francisco, CA-based roles: The base salary range for this role is USD $202,000 per year - USD $224,000 per year.

You will be eligible to participate in Uber's bonus program, and may be offered an equity award & other types of comp.

All full-time employees are eligible to participate in a 401(k) plan.

You will also be eligible for various benefits.

Ready to Ride?

This isn't the kind of place where you follow a playbook — it's where you help write one.

If you're driven by impact, energized by challenge, and ready to shape how the world moves — we'd love to hear from you.

You may be eligible for bonuses, equity, and other compensation, as well as a range of benefits.

Explore our benefits.

Offices remain key to collaboration and Uber's culture.

Unless approved for full remote work, employees must spend at least 50% of their time in-office.

Some roles, like those at greenlight hubs, require full-time in-office presence.

Ask your Recruiter for details about this role's requirements.

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.

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