Chaitanya Kusumanchi

Key Skills

Software

Internal/Proprietary Tooling

Snorkel AI

Scale AI

Top Subject Matter

No subject matter listed

Top Data Types

3D Sensor

Audio

Computer Code Programming

Document

Geospatial Tiled Imagery

Image

Text

Top Label Types

Action Recognition

Bounding Box

Classification

Computer Programming Coding

Entity Ner Classification

Evaluation Rating

Fine Tuning

Function Calling

Object Detection

Prompt Response Writing SFT

Red Teaming

RLHF

Segmentation

Text Summarization

Translation Localization

Freelancer Overview

I have a strong background in AI development and data science, with hands-on experience in building and fine-tuning large language models (LLMs), developing computer vision and NLP solutions, and deploying end-to-end AI pipelines. My work spans data annotation, training data preparation, and integrating AI models into real-world applications, including conversational agents, generative AI, and custom object detection systems. I am skilled in Python, TensorFlow, PyTorch, Hugging Face, and a range of data engineering and MLOps tools, allowing me to manage the full lifecycle of datasets—from collection and labeling to validation and deployment. My experience includes projects in domains such as e-commerce, robotics, and healthcare, where I have designed scalable data workflows and contributed to patent-pending innovations involving NLU and computer vision. I am passionate about ensuring high-quality, well-annotated data to drive impactful AI solutions.

Labeling Experience

AI expert (project calibrator, pod lead/reviewer)

Internal Proprietary ToolingTextRLHF

As an AI expert for Turing, I contributed to supervised fine-tuning (SFT) and reinforcement learning from human feedback (RLHF) projects for NVIDIA. My responsibilities included calibrating project outputs, reviewing AI-generated results, and leading or reviewing teams on assigned pods. I worked with text data to improve large language model capabilities for enterprise needs. • Oversaw data labeling and training for SFT and RLHF tasks. • Ensured high-quality review and calibration of AI outputs. • Led or reviewed teams in data annotation pods. • Focused on optimizing data quality for advanced LLMs.

As an AI expert for Turing, I contributed to supervised fine-tuning (SFT) and reinforcement learning from human feedback (RLHF) projects for NVIDIA. My responsibilities included calibrating project outputs, reviewing AI-generated results, and leading or reviewing teams on assigned pods. I worked with text data to improve large language model capabilities for enterprise needs. • Oversaw data labeling and training for SFT and RLHF tasks. • Ensured high-quality review and calibration of AI outputs. • Led or reviewed teams in data annotation pods. • Focused on optimizing data quality for advanced LLMs.

2025

AI expert (contributor, reviewer)

Snorkel AITextRLHF

At Snorkel AI, I worked as an AI expert focused on contributing to and reviewing terminal bench tasks and RLHF/SFT projects. My duties involved labeling and reviewing extensive language model training datasets. I was responsible for maintaining the integrity and quality of labeled data in large-scale training initiatives. • Labeled and reviewed 450+ terminal bench tasks. • Participated in SFT and RLHF data annotation. • Collaborated in team reviews for continuous quality improvement. • Contributed to large language model evaluation and benchmarking.

At Snorkel AI, I worked as an AI expert focused on contributing to and reviewing terminal bench tasks and RLHF/SFT projects. My duties involved labeling and reviewing extensive language model training datasets. I was responsible for maintaining the integrity and quality of labeled data in large-scale training initiatives. • Labeled and reviewed 450+ terminal bench tasks. • Participated in SFT and RLHF data annotation. • Collaborated in team reviews for continuous quality improvement. • Contributed to large language model evaluation and benchmarking.

2025

AI expert (contributor, reviewer, Pod lead)

Scale AITextRLHF

As an AI expert at Outlier AI, I worked on a variety of LLM-related projects including SFT, RLHF, MCP, Datascience, OTS, and evaluation tasks. I contributed to and reviewed labeled training data for supervised and reinforcement learning methods. My duties also involved leading pods and ensuring datasets met evaluation criteria. • Led and reviewed SFT and RLHF annotation tasks. • Oversaw data quality for multiple AI evaluation projects. • Conducted MCP, Datascience, and OTS annotations. • Supported continual improvement of labeled datasets for LLM research.

As an AI expert at Outlier AI, I worked on a variety of LLM-related projects including SFT, RLHF, MCP, Datascience, OTS, and evaluation tasks. I contributed to and reviewed labeled training data for supervised and reinforcement learning methods. My duties also involved leading pods and ensuring datasets met evaluation criteria. • Led and reviewed SFT and RLHF annotation tasks. • Oversaw data quality for multiple AI evaluation projects. • Conducted MCP, Datascience, and OTS annotations. • Supported continual improvement of labeled datasets for LLM research.

2024

AI expert (contributor)

Internal Proprietary ToolingTextRLHF

During my time at AfterQuery Experts, I served as an AI expert contributing to terminal bench tasks for LLM training projects. My work centered on annotating and reviewing language data for supervised fine-tuning and reinforcement learning purposes. I collaborated closely on team-based annotation projects involving complex language understanding. • Labeled and reviewed 200+ terminal bench tasks. • Focused on SFT and RLHF annotation. • Maintained high data accuracy standards. • Supported robust training set preparation for LLMs.

During my time at AfterQuery Experts, I served as an AI expert contributing to terminal bench tasks for LLM training projects. My work centered on annotating and reviewing language data for supervised fine-tuning and reinforcement learning purposes. I collaborated closely on team-based annotation projects involving complex language understanding. • Labeled and reviewed 200+ terminal bench tasks. • Focused on SFT and RLHF annotation. • Maintained high data accuracy standards. • Supported robust training set preparation for LLMs.

2025 - 2025

Education

Work History