Manoj Gowda

Key Skills

Software

Snorkel AI

Top Subject Matter

AI Model Training

Weak Supervision

Dataset Validation

Top Data Types

Text

Computer Code Programming

Top Task Types

Fine-tuning

Freelancer Overview

AI Model Evaluation & Data Engineering Contributor. Brings 2+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include Snorkel AI, Internal, and Proprietary Tooling. Education includes Bachelor of Engineering, Visvesvaraya Technological University (2024). AI-training focus includes data types such as Text, Computer Code, and Programming and labeling workflows including Fine-tuning, Evaluation, and Rating.

Labeling Experience

Claude Code Training & Evaluation Specialist

I evaluated AI-generated multi-file codebases to assess architectural correctness and system determinism. Realistic engineering scenarios and reproducible test harnesses were built to validate code generation outcomes. Documentation clarity and test coverage of AI-generated code were critically assessed in containerized environments. • Evaluated complex AI-generated code for conformance to engineering standards • Designed challenging testing scenarios reflecting real-world software projects • Built automated systems to assess code reproducibility and correctness • Verified documentation and test coverage for AI-generated solutions

I evaluated AI-generated multi-file codebases to assess architectural correctness and system determinism. Realistic engineering scenarios and reproducible test harnesses were built to validate code generation outcomes. Documentation clarity and test coverage of AI-generated code were critically assessed in containerized environments. • Evaluated complex AI-generated code for conformance to engineering standards • Designed challenging testing scenarios reflecting real-world software projects • Built automated systems to assess code reproducibility and correctness • Verified documentation and test coverage for AI-generated solutions

2025 - 2026

AI Model Evaluation & Data Engineering Contributor

Snorkel AITextFine Tuning

I contributed to weak supervision workflows supporting AI model training and data validation. Structured labeling functions and validation pipelines were created to promote reproducibility in AI datasets. My responsibilities included error analysis, dataset refinement, and documenting consistent evaluation methodologies. • Developed and implemented labeling functions for supervised model improvement • Built pipelines to validate labeled datasets and ensure accuracy • Conducted thorough error analysis and curated datasets for better evaluation • Authored standardized documentation guiding experimentation processes

I contributed to weak supervision workflows supporting AI model training and data validation. Structured labeling functions and validation pipelines were created to promote reproducibility in AI datasets. My responsibilities included error analysis, dataset refinement, and documenting consistent evaluation methodologies. • Developed and implemented labeling functions for supervised model improvement • Built pipelines to validate labeled datasets and ensure accuracy • Conducted thorough error analysis and curated datasets for better evaluation • Authored standardized documentation guiding experimentation processes

2024 - 2024

Education

Work History