Senior Machine Learning Engineer - Applied AI

Uber Uber · Consumer · Bangalore, India · Engineering

Senior ML Engineer role focused on building and deploying production-ready ML systems, including generative AI, computer vision, and personalization, to power core Uber products. The role involves the full ML lifecycle from experimentation to monitoring and emphasizes delivering end-to-end AI solutions.

What you'd actually do

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

Skills

Required

  • Python
  • Tensorflow
  • PyTorch
  • JAX
  • Scikit-Learn
  • SQL
  • Hive
  • Kafka
  • Cassandra
  • ML development lifecycle
  • responsible AI

Nice to have

  • generative AI
  • LLMs
  • diffusion models
  • modern deep learning architectures
  • probabilistic models
  • large-scale ML systems

What the JD emphasized

  • production-ready ML systems
  • ML solutions at scale
  • delivering end-to-end AI solutions

Other signals

  • delivering end-to-end AI solutions
  • building ML solutions that power core user and business-facing products
  • delivering high-quality, production-ready ML systems and infrastructure
  • development, training, productionization and monitoring of ML solutions at scale