AI / ML Consultant

1 month ago

Pune, India Quantum Integrators Full time

AI / ML Consultant


Main responsibilities :


  • Develop and support AI/ML solution using best in-class LLM/DL/ML models and statistical techniques.
  • Perform code development, Unit testing, System testing, and debugging HPE's applications.
  • Collaborate with business users, understand requirements, develop design specifications and develop IT solutions for support and strategic projects.
  • Support the decision making related to optimal systems landscape in constantly changing environment.
  • Resolve production support issues and work towards reduction of support incidents through implementation of long term and sustainable fixes.

Knowledge and Skills:


  • Deep familiarity across the stack – compute infrastructure, ML frameworks, orchestration layers, large models, frameworks like Langchain for developing applications powered by GenAI models, MLOPs, as well as target use cases in the cloud.
  • Experience with GenAI models across training, inference, MLOPs, and/or developing GenAI applications.
  • Experience with data engineering techniques and different platforms including vector DB & knowledge graphs.
  • Experience with one or more general purpose programming languages, including but not limited to: C/C++, C#, Python.
  • Experience training large models across compute types and developing applications powered by GenAI models.
  • Experience with prompt engineering and the ability to craft effective prompts for various applications.
  • Familiarity with ethical considerations in AI development and deployment.
  • Excellent written and verbal communication skills, with the ability to explain complex technical concepts to non-technical audiences.
  • Ability to work alone and as part of a team in a fast-paced environment.
  • Experience with cloud computing platforms like AWS, Azure, or GCP.
  • Experience in training and optimizing Generative AI models (GANs, VAEs, diffusion models, etc.) is a plus.
  • Hands-on understanding of deep learning, loss functions, and optimization techniques and other ML algorithms and infrastructure is a plus.

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