Vishnu Chaitanya Goddeti

Key Skills

Software

Labelbox

CrowdSource

CVAT

Google Cloud Vertex AI

Label Studio

Scale AI

Top Subject Matter

Quality Assurance, Quality Reviewer

STEM, Coding, Multimodal Domain Expert

Computer Vision, Image and Video Expert

Top Data Types

Image

Computer Code Programming

Text

Top Task Types

Question Answering

Classification

Prompt + Response Writing (SFT)

Text Generation

Text Summarization

RLHF

Red Teaming

Evaluation/Rating

Computer Programming/Coding

Transcription

Object Detection

Bounding Box

Segmentation

Entity (NER) Classification

Fine-tuning

Data Collection

Function Calling

Cuboid

Freelancer Overview

I have 3+ years of experience in AI training data, data labeling, RLHF evaluation, and quality review across NLP, vision, multimodal, STEM, and coding-related AI projects. In my recent role as an Advanced AI Data Trainer and QA Reviewer at Invisible Technologies, I evaluated AI model responses using structured rubrics, reviewed annotated datasets for correctness and consistency, performed image description annotation and multimodal labeling, and helped validate ground-truth outputs for AI training pipelines. My background also includes GenAI model training at Outlier AI, where I worked on prompt engineering, response evaluation, safety/relevance checks, and RLHF workflows for improving model alignment. What sets me apart is my strong combination of technical knowledge and annotation quality experience. I have worked on large-scale image and video annotation review with Alignerr-Labelbox, designed high-difficulty STEM datasets as an AI Trainer, and used Python-based validation methods to support model reasoning and evaluation workflows. I am skilled at identifying reasoning errors, checking edge cases, following strict project guidelines, writing clear feedback, and maintaining high-quality standards across client-facing AI data projects. My foundation in AI/ML, prompt engineering, cloud tools, DevOps, and programming helps me understand both the data quality side and the technical impact of training data on production-grade AI systems.

Labeling Experience

Advanced AI Data Trainer → QA Reviewer

TextRLHF

As an Advanced AI Data Trainer and QA Reviewer, I performed structured evaluation and quality scoring of AI model responses. My work focused on reviewing annotated datasets and model evaluation tasks for correctness and consistency, aligning with RLHF and data annotation standards. I carried out data annotation tasks including image description, multimodal labeling, and dataset validation to support AI training pipelines. • Performed detailed model response assessments using evaluation rubrics. • Ensured correctness and compliance in annotated datasets and evaluation tasks. • Participated in RLHF workflows and validated reasoning and outputs. • Automated validation and contributed to Python-based model evaluation projects.

As an Advanced AI Data Trainer and QA Reviewer, I performed structured evaluation and quality scoring of AI model responses. My work focused on reviewing annotated datasets and model evaluation tasks for correctness and consistency, aligning with RLHF and data annotation standards. I carried out data annotation tasks including image description, multimodal labeling, and dataset validation to support AI training pipelines. • Performed detailed model response assessments using evaluation rubrics. • Ensured correctness and compliance in annotated datasets and evaluation tasks. • Participated in RLHF workflows and validated reasoning and outputs. • Automated validation and contributed to Python-based model evaluation projects.

2025 - Present

STEM Expert – AI Trainer

TextQuestion Answering

As a STEM Expert – AI Trainer, I created and verified high-difficulty STEM questions and structured solutions for model evaluation. I designed step-by-step reasoning paths and reviewed datasets to ensure analytical rigor and adherence to quality rubrics. My role involved providing structured feedback to improve AI problem-solving and dataset robustness. • Developed computation-heavy problems in math, physics, and computer science. • Led quality review and ensured dataset integrity and difficulty calibration. • Identified logical gaps in model responses for robust AI training. • Collaborated with reviewers and research teams for data quality.

As a STEM Expert – AI Trainer, I created and verified high-difficulty STEM questions and structured solutions for model evaluation. I designed step-by-step reasoning paths and reviewed datasets to ensure analytical rigor and adherence to quality rubrics. My role involved providing structured feedback to improve AI problem-solving and dataset robustness. • Developed computation-heavy problems in math, physics, and computer science. • Led quality review and ensured dataset integrity and difficulty calibration. • Identified logical gaps in model responses for robust AI training. • Collaborated with reviewers and research teams for data quality.

2025 - 2025

Code Reviewer – Data Annotation

LabelboxImageClassification

As a Code Reviewer for Data Annotation, I led quality reviews of large-scale image and video datasets for vision-based AI models. I evaluated annotation consistency and model outputs, ensuring systematic error identification and improvement of annotation reliability. My responsibilities included providing feedback on edge cases and contributing to annotation process refinements. • Reviewed image and video annotation datasets to meet accuracy benchmarks. • Identified and resolved systematic errors in model outputs. • Improved annotation and reviewer calibration for project success. • Coordinated reviews to meet timelines and evolving requirements.

As a Code Reviewer for Data Annotation, I led quality reviews of large-scale image and video datasets for vision-based AI models. I evaluated annotation consistency and model outputs, ensuring systematic error identification and improvement of annotation reliability. My responsibilities included providing feedback on edge cases and contributing to annotation process refinements. • Reviewed image and video annotation datasets to meet accuracy benchmarks. • Identified and resolved systematic errors in model outputs. • Improved annotation and reviewer calibration for project success. • Coordinated reviews to meet timelines and evolving requirements.

2024 - 2025

GenAI Model Trainer (Prompt Engineer)

TextPrompt Response Writing SFT

As a GenAI Model Trainer (Prompt Engineer), I developed and evaluated prompt frameworks for generative NLP models. My work included RLHF pipeline contributions, refining evaluation criteria and domain-specific prompt generation to improve model behavior. I collaborated closely with teams and clients to iterate on prompt designs and evaluation strategies. • Designed prompt-based assessment frameworks for LLM/NLP models. • Contributed to RLHF by analyzing and rating AI outputs. • Customized evaluation for enterprise and government NLP use cases. • Iteratively improved prompt design with cross-functional input.

As a GenAI Model Trainer (Prompt Engineer), I developed and evaluated prompt frameworks for generative NLP models. My work included RLHF pipeline contributions, refining evaluation criteria and domain-specific prompt generation to improve model behavior. I collaborated closely with teams and clients to iterate on prompt designs and evaluation strategies. • Designed prompt-based assessment frameworks for LLM/NLP models. • Contributed to RLHF by analyzing and rating AI outputs. • Customized evaluation for enterprise and government NLP use cases. • Iteratively improved prompt design with cross-functional input.

2023 - 2025

Education

Work History