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Lead Generative AI Engineer

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Hybrid

Lead Generative AI Engineer

Capgemini

Lead Generative AI Engineer

Skills

Deep LearningFlaskPythonNumPypandasPyTorchTensorFlowMachine LearningAIFastAPIPySparkSupply Chain

2 months ago

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Important information


Contract type:

Permanent

Location:

Bengaluru, Karnataka, India

Work mode:

Hybrid

Published on:

19 August 2026

What they need


Responsibilities:

  • Lead and conduct advanced research in generative AI, focusing on GANs, VAEs, and other state-of-the-art models.
  • Develop innovative algorithms and techniques to push the boundaries of generative AI.
  • Collaborate with interdisciplinary teams to apply generative models in various domains such as healthcare, finance, Power & utility, manufacturing and supply chain.
  • Design, develop, and deploy generative AI models for complex real-world applications.
  • Optimize models for performance, scalability, and robustness.
  • Implemented multimodal , Multi Agent/ Agentic AI in Gen AI.
  • Work closely with research scientists to implement cutting-edge generative algorithms.
  • Lead a team of engineers, providing technical guidance and mentorship.
  • Develop and maintain AI pipelines for data processing, model training, and deployment.
  • Conduct thorough testing and validation of models to ensure high-quality outputs.
  • Mentor junior researchers and guide their projects.
  • Publish high-impact research papers in top-tier conferences and journals.
  • Stay abreast of the latest trends and advancements in AI and machine learning.

Qualifications:

  • Ph.D./Engineering /MCA in Computer Science, Machine Learning, or a related field.
  • 6-10 years of experience in AI research, with a strong focus on generative models.
  • Proven track record of publications in reputable conferences and journals.
  • Proficiency in programming languages such as Python and deep learning frameworks like TensorFlow or PyTorch.
  • Experience with large-scale data processing and model training.
  • Strong analytical and problem-solving skills.
  • Excellent communication and collaboration skills.
  • At least 5+ years of experience in Python/ Pyspark with hands on delivery experience; Pandas/ NumPy, TensorFlow, Flask/ FastAPI, scikit-learn

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