Senior Machine Learning Engineer
UberBangalore, IndiaPosted 5 March 2026
Job Description
Senior Machine Learning Engineer
Department: Engineering
Team: Machine Learning
Location: Bangalore, India
Type: Full-Time
## Your Role & Mission
We are looking for a highly motivated Machine Learning Engineer to join the Customer Obsession team. You will play a critical role in designing systems and algorithms which would enhance the customer support experience and resolution speed for millions of Uber users worldwide while also unlocking O(100s millions USD) in 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 You'll Be Working On
1. Design, develop, and productionize machine learning (ML) 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. Mentor junior engineers.
## Required Qualifications
01. Bachelor's or Master's in Computer Science, Statistics, or a related field or Equivalent Experience
02. Minimum 6 years of experience in industry with a strong focus on machine learning and optimization.
03. Experience with ML packages such as Tensorflow, PyTorch, JAX, and Scikit-Learn.
04. Solid understanding of statistical analysis and feature engineering techniques.
05. Excellent communication and collaboration skills.
06. Ability to work independently and take ownership of projects.
07. Experience using SQL in a production environment.
08. Experience in experimental design and analysis, exploratory data analysis, and statistical anal
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