ML Engineer II

• Uber AI Solutions is one of Uber's biggest bets with the ambition to build one of the world's largest data foundries for AI applications and evolve into a platform of choice for a variety of online tasks. The Moonshot AI team focuses on optimizing the Uber AI Solutions gig marketplace through intelligent supply and demand matching. We also accelerate human-in-the-loop data annotation with automation and develop robust automated evaluation systems.
• We are in the early stages, with significant opportunities to build new ML models for the gig marketplace. This includes integrating advanced ML models to enable ML-assisted annotations for various use cases, such as Gen AI Labeling, Image/Audio/Video Classification, and Image/Video Segmentation, building LLM-as-Judge for automated quality evaluation, training ranking models to recommend gigs to earners, etc..
• In this role, you will collaborate closely with product managers, program managers, and cross-functional teams to deliver real world impact. You'll help grow Uber AI Solutions into a leader in the space.

What the Candidate Will Need / Bonus Points

 What the Candidate Will Do

1. Design and develop large-scale machine learning models systems
2. Collaborate with backend and frontend engineers to integrate your solutions into our products & platforms.
3. Write clean, modular, and maintainable code.
4. Conduct code reviews and ensure high code quality standards.
5. Keep up to date with the latest ML technologies and best practices.

 Basic Qualifications

1. Ph.D., MS, or Bachelors degree in Computer Science or a closely related discipline.
2. Proficiency in Computer Vision (CV), Natural Language Processing (NLP), or Deep Learning, with a solid grasp of the latest advancements in Generative AI.
3. Exceptional coding skills, demonstrated by the ability to write clean, elegant, and bug-free code in languages such as Java or Go.
4. Strong desire for continuous learning and professional growth, coupled with a commitment to developing best-in-class systems.
5. Excellent problem-solving and analytical abilities.
6. Proven ability to collaborate effectively as a team player

 Preferred Qualifications

1. 2+ years of industry experience in ML/AI.
2. Proven track record of training large models on distributed infrastructure.
3. Demonstrated ability to rapidly prototype, signaling curiosity and an experimental approach.
4. Experience collaborating effectively across an organization, not limited to just within teams.