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ZEISS India Linkedin · Posted 27d ago

Research Engineer – AI/ML

Bengaluru, Karnataka, India

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Job Summary

We are seeking a highly motivated and skilled Research Engineer with 2+ years of experience in AI/ML to join our dynamic R&D team. The ideal candidate is passionate about applied machine learning, has strong algorithmic thinking, and possesses excellent communication skills. The role offers an exciting opportunity to work on cutting-edge research and contribute to real-world applications.


Key Responsibilities

  • Design, develop, and optimize algorithms in AI/ML for real-world applications.
  • Conduct research and experiments to solve open-ended engineering problems.
  • Collaborate with cross-functional teams to define problem statements and develop technical solutions.
  • Prototype, validate, and scale AI/ML models using Python and related frameworks.

Contribute to technical documentation, research papers, and presentations.

  • Stay up-to-date with the latest developments in machine learning and related fields.
  • Develop and enhance rendering techniques to produce photorealistic images and animations, utilizing advanced shading, lighting, and texturing methods


Required Qualifications

  • 2+ years of hands-on experience in AI/ML, data science, or related areas. Deep learning, machine learning, recurrent learning, 3D CNNs, foundation models (good to have)
  • Hands on conventional and AI-based Image processing.
  • Proficiency in Python and ML frameworks (e.g., TensorFlow, PyTorch, scikit-learn).
  • Optimization and pruning of AI algorithms
  • Knowledge of Git


Educational Requirements

  • Completed or currently in the final stages of a Ph.D. program in one of the following disciplines:
  • Medical Electronics
  • Biomedical Engineering
  • Computational data science
  • Computer Science
  • Artificial Intelligence / Machine Learning
  • Electronics or Electrical Engineering
  • Information Science
  • Related engineering fields


Preferred Qualifications

  • Experience with research publication, internships, or projects in AI/ML.
  • Exposure to domain-specific AI applications (e.g., healthcare, signal/image processing, embedded AI).
  • Familiarity with scientific computing tools and environments.
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