GenAI Engineer

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 that will enhance the customer support experience and resolution speed for millions of Uber Eats users worldwide while making O(100s of millions) in cost savings. You will leverage your expertise in data analysis, machine learning, and engineering to drive insights, identify tech-driven product innovations, and optimise algorithms and systems, ultimately improving user satisfaction and operational efficiency.
Responsibilities:
Design, develop, and productionise 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.
Productionise and deploy these models for real-world applications in customer support.
Design and analyse experiments using a combination of data analysis/statistical analysis to lead the team to a reasonable inference.
Review code and designs of teammates, providing constructive feedback.
Collaborate with cross-functional teams to brainstorm new solutions and iterate on the product.
Technically lead the team, mentor and guide engineers
Requirements:
Experience in building and owning Conversational GenAI models over multiple years.
Strong understanding of product and operational metrics and what it takes to improve them.
Bachelor's or Master's in computer science, statistics, or a related field.
Equivalent Experience in Conversational GenAI.
Minimum 10+ years of experience in the industry with a strong focus on machine learning and optimisation.
Experience with ML packages such as Tensorflow, PyTorch, JAX, and Scikit-Learn.
Solid understanding of statistical analysis and feature engineering techniques.
Excellent communication and collaboration skills.
Ability to work independently and take ownership of projects.
Experience using SQL in a production environment.
Experience in experimental design and analysis, exploratory data analysis, and statistical analysis.
Experience with dashboarding and using data visualisation tools.
Experience using statistical methodologies such as sampling, statistical estimates, descriptive statistics, or similar.

Experience
10-14 yrs