Senior Machine Learning Engineer Job at Uber (Bangalore)

Senior Machine Learning Engineer

Uber

Location:
India , Bangalore

Category:
IT - Software Development

Contract Type:
Not provided

Salary:

Not provided

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Job Description:

Applied AI is a horizontal AI team at Uber collaborating with business units across the company to deliver cutting-edge AI solutions for core business problems. We work closely with engineering, product and data science teams to understand key business problems and the potential for AI solutions, then deliver those AI solutions end-to-end. Key areas of expertise include Generative AI, Computer Vision, and Personalization. We are looking for a strong Senior ML engineer to be a part of a high-impact team at the intersection of classical machine learning, generative AI, and ML infrastructure. In this role, you’ll be responsible for delivering Uber’s next wave of intelligent experiences by building ML solutions that power core user and business-facing products.

Job Responsibility:

Solve business-critical problems using a mix of classical ML, deep learning, and generative AI
Collaborate with product, science, and engineering teams to execute on the technical vision and roadmap for Applied AI initiatives
Deliver high-quality, production-ready ML systems and infrastructure, from experimentation through deployment and monitoring
Adopt best practices in ML development lifecycle (e.g., data versioning, model training, evaluation, monitoring, responsible AI)
Deliver enduring value in the form of software and model artifacts

Requirements:

Master or PhD or equivalent experience in Computer Science, Engineering, Mathematics or a related field and 2 years of Software Engineering work experience, or 5 years Software Engineering work experience
Experience in programming with a language such as Python, C, C++, Java, or Go
Experience with ML packages such as Tensorflow, PyTorch, JAX, and Scikit-Learn
Experience with SQL and database systems such as Hive, Kafka, and Cassandra
Experience in the development, training, productionization and monitoring of ML solutions at scale
Strong desire for continuous learning and professional growth, coupled with a commitment to developing best-in-class systems
Excellent problem-solving and analytical abilities
Proven ability to collaborate effectively as a team player

Nice to have:

Prior experience working with generative AI (e.g., LLMs, diffusion models) and integrating such technologies into end-user products
Experience in modern deep learning architectures and probabilistic models
Machine Learning, Computer Science, Statistics, or a related field with research or applied focus on large-scale ML systems

Additional Information:

Job Posted:
March 19, 2026

Work Type:

On-site work

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