Senior ML Engineer: Scalable AI for Consumer Growth

Uber; Seattle (WA); On-site; USD 202,000 - 224,000; Full time

Benefits offered by this job

Bonus program

Equity award

401(k) plan

Benefits

Job summary

Uber is seeking a senior engineer to build products powered by scalable distributed systems and AI solutions. You will optimize user experiences across grocery and food verticals while driving sustainable business growth. You will own architectures, guide end-to-end lifecycles, and collaborate with product, operations, and data science teams.

The role emphasizes designing high-scale ML systems, strong ownership, and cross-functional collaboration, with in-office requirements at many US locations.

Qualifications

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

Responsibilities

• Architecting and launching products to power key consumer experience and business outcomes.
• Overseeing full project lifecycles spanning initial scoping, offline evaluation, experimental testing, production deployment, and post-launch maintenance.
• Designing, tuning, and enhancing systems and algorithms to operate at scale.
• Partnering with cross-functional stakeholders across product management, operations, and data science

Skills

Communication

Ownership

Cross-functional collaboration

Mentoring

Education

Bachelor’s degree in CS/Engineering/Math or related field

Tools

Python

Go

Java

Job description

Uber is seeking a senior engineer to build products powered by scalable distributed systems and AI solutions. You will optimize user experiences across grocery and food verticals while driving sustainable business growth. You will own architectures, guide end-to-end lifecycles, and collaborate with product, operations, and data science teams.

The role emphasizes designing high-scale ML systems, strong ownership, and cross-functional collaboration, with in-office requirements at many US locations.