AI/ ML Application Technical Analyst

3 days ago


Mumbai, Maharashtra, India Tata Consultancy Services Full time

AI/ML, GENAI, NLP, Deep Learning, LLM Models

AI/ ML Application Technical Analyst

Required Technical Skill Set**

  • Overall Experience: 5+ Years of experience in development/triaging/debugging roles
  • AI/ML Knowledge: 2+ years' experience with common AI/ML algorithms, architectures, tools, and practices. Familiarity with model training, inference, and quantization.
  • AI/ ML Frameworks: Knowledge about PyTorch, ONNX, TensorFlow and any other framework
  • AI/ ML Model Repositories: Familiarity with repositories like Huggingface, Ultralytics, FuxiCTR
  • Technical Verification: Familiarity with software or model verification processes, ensuring that software/models meet specified requirements.

Desired Competencies (Technical/Behavioral Competency)

Must-Have**

(Ideally should not be more than 3-5)

  • Overall Experience: 5+ Years of experience in development/triaging/debugging roles
  • AI/ML Knowledge: 2+ years' experience with common AI/ML algorithms, architectures, tools, and practices. Familiarity with model training, inference, and quantization.
  • AI/ ML Frameworks: Knowledge about PyTorch, ONNX, TensorFlow and any other framework
  • AI/ ML Model Repositories: Familiarity with repositories like Huggingface, Ultralytics, FuxiCTR
  • Technical Verification: Familiarity with software or model verification processes, ensuring that software/models meet specified requirements.
  • Python and/or C/C++ programming
  • Linux and shell script
  • GitHub
  • Dockers/ Kubernetes/ Containers

Good-to-Have

  • Understanding of installing Linux/Windows drivers and debugging failures of drivers
  • Knowledge about regression testing/ verification tools
  • Debugging code to pin-point areas of problems
  • Working with end users to address their questions, debugging their problems and documenting solutions.
  • CI/ CD tools and pipeline
  • Experience with DevOps and CI/CD practices.
  • Experience with data engineering and machine learning pipelines.

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