Nandhu S KumarAI & MACHINE LEARNING
03 / Experience

Work
experience.

Software engineering and machine learning roles, with work on Python applications, model evaluation, and deployment.

2026
AUG 2026 TO PRESENT
REMOTE / USA

AI Fellow (AI Trainer)

Handshake AI · USA

Contribute to the Handshake AI Fellowship, supporting AI research through human evaluation of large language models. Focus on identifying where and how models struggle with tasks involving real datasets.

  • Dataset Sourcing & Review: Source dataset files across different domains and formats. Examine their content, structure, and suitability for challenging model interpretation and analysis.
  • Prompt Development & Testing: Develop prompts grounded in the selected datasets to test complex reasoning and instruction following. Run these prompts and collect model outputs for assessment.
  • Output Validation & Failure Analysis: Check responses against source data and task requirements. Document incorrect interpretations, reasoning errors, unsupported conclusions, and incomplete results through structured feedback to support model improvement.
Technologies & methods
  • Dataset review
  • Prompt testing
  • LLM evaluation
2022 to 24
MARCH 2022 to AUGUST 2024
PART TIME / REMOTE / INDIA

Junior Software Engineer

ITSoleX India · Mumbai

Worked remotely for 2.5 years, developing and maintaining Python applications with the engineering team.

  • Developed Python web applications using Flask and Django, with REST APIs, data validation, database integration, and business logic for inventory and operational workflows.
  • Integrated scikit-learn, PyTorch, and OpenCV for selected image classification and document data extraction tasks.
  • Contributed to AWS deployments, Docker packaging, and CI/CD application release pipelines.
  • Supported production troubleshooting, configuration changes, and routine application updates.
Technologies & methods
  • Python
  • Flask
  • Django
  • PyTorch
  • AWS
  • Docker
2024
SEPTEMBER to DECEMBER
MACHINE LEARNING INTERNSHIP

Machine Learning Intern

Unified Mentor · India

Developed complete machine learning pipelines, from preprocessing and feature engineering to training and model evaluation.

  • Worked with datasets containing more than 15,000 records.
  • Designed pipelines covering preprocessing, feature engineering, and model evaluation.
  • Developed and optimized PyTorch models, achieving approximately 18% improvement over the project baselines.
Technologies & methods
  • PyTorch
  • Feature engineering
  • Model evaluation
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