Staff ML Engineer - GenAI

Staff ML Engineer - GenAI Department: Engineering Team: Machine Learning Location: Bangalore, India Type: Full-Time **About the Role** We are looking for a highly motivated GenAI Engineer to join the Customer Obsession team. You will play a critical role in designing conversational GenAI systems and algorithms which would enhance the customer support experience and resolution speed for millions of Uber Eats users worldwide while making O(100s millions) cost savings. You will leverage your expertise in data analysis, machine learning, and engineering to drive insights, identify tech-driven product innovations, optimize algorithms and systems ultimately improving user satisfaction and operational efficiency. **What the Candidate Will Do:** 1. Design, develop, and productionize Conversational GenAI solutions in the field of customer support engineering spanning generative AI algorithms, agentic AI design at scale, NLP for query understanding and ranking responses, distillation techniques, etc. 2. Productionize and deploy these models for real-world applications in customer support. 3. Design and analyze experiments using a combination of data analysis/statistical analysis to lead the team to a reasonable inference. 4. Review code and designs of teammates, providing constructive feedback. 5. Collaborate with cross-functional teams to brainstorm new solutions and iterate on the product. 6. Technically lead the team, mentor and guide engineers **What the Candidate Will Need:** 01. Experience in building and owning Conversational GenAI models over multiple years, including strong understanding of product and operational metrics and what it takes to improve them. 02. Bachelor's or Master's in Computer Science, Statistics, or a related field or Equivalent Experience in Conversational GenAI 03. Minimum 10+ years of experience in industry with a strong focus on machine learning and optimization. 04. Experience with ML packages such as Tensorflow, PyTorch, JAX, and Scikit-Learn. 05. Solid understanding of statistical analysis and feature engineering techniques. 06. Excellent communicati