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Job Description

Uber’s Consumer Incentives team builds AI-powered optimizations and distributed systems that shape consumer experiences across verticals including grocery and food. In this Sr Machine Learning Engineer role, you will work on end-to-end machine learning product lifecycle development, moving from early scoping and offline evaluation to production deployment and ongoing post-launch maintenance.

Role focus

  • Architect and launch products that drive key consumer experience and business outcomes.
  • Own the full project lifecycle, including scoping, offline evaluation, experimental testing, production deployment, and post-launch maintenance.
  • Design, tune, and improve systems and algorithms to support large-scale operation.
  • Collaborate with cross-functional partners across product management, operations, and data science.

What you bring

  • Bachelor’s degree or equivalent in Computer Science, Engineering, Mathematics, or a related field, plus 4+ years of full-time engineering experience.
  • Proficiency in at least one programming language such as Python, Go, or Java.
  • Experience building and productionizing end-to-end machine learning systems.
  • Strong communication skills and the ability to work effectively with cross-functional partners.
  • A strong ownership mindset to drive projects end-to-end.

Technologies

  • Python
  • Go
  • Java

Preferred qualifications

  • A track record of designing and delivering large-scale consumer products.
  • Demonstrated leadership skills, including experience mentoring and guiding junior engineers.
  • Proven experience in experimental design and causal inference.

Compensation and location

This role is based in New York, NY (onsite). The base salary range is USD $202,000 - $224,000 per year.

Benefits

  • Eligibility to participate in Uber’s bonus program (for all US locations).
  • May be offered an equity award and other types of compensation (for all US locations).
  • All full-time employees are eligible to participate in a 401(k) plan.
  • Eligibility for various benefits.

Office expectations

  • Unless approved for full remote work, employees must spend at least 50% of their time in-office.
  • Some roles, such as those at greenlight hubs, require full-time in-office presence.
  • Ask your Recruiter for details about this role’s requirements.

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