Carbanak

Key Skills

Software

Scale AI

Top Subject Matter

AI model evaluation

Grading Domain Expertise

and annotation systems

Top Data Types

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Top Task Types

No task types listed

Freelancer Overview

Full-Stack Software Engineer, Outlier AI (AI evaluation & grading/annotation tooling). Brings 5+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include Internal, Proprietary Tooling, and Scale AI. Education includes Doctor of Philosophy, MIT (Massachusetts Institute of Technology) (2026) and Master of Science, MIT (Massachusetts Institute of Technology) (2023). AI-training focus includes data types such as Text and labeling workflows including Evaluation and Rating.

Labeling Experience

Senior Full-Stack / AI Engineer - Nexus AI

Scale AIText

Senior Full-Stack / AI Engineer building scalable backend systems and full-stack applications for AI model evaluation workflows. Responsible for designing and deploying REST APIs, distributed processing components, and performance optimizations for real-time AI services. Applies strong Python, FastAPI, and cloud-native architecture skills to improve reliability and throughput of production systems. • Designed backend services to support AI evaluation workflows and distributed processing • Built RESTful APIs and full-stack applications using Python, FastAPI, Next.js, PostgreSQL, and Redis • Optimized API response performance and backend throughput for real-time AI systems • Evaluated AI model outputs and supported prompt optimization and model reliability initiatives

2025 - Present

Full-Stack Software Engineer - Outlier AI

Scale AIText

Full-Stack Software Engineer developing internal dashboards and evaluation tools for AI assessment workflows. Led the implementation of scalable backend services, data pipelines, and asynchronous processing to support grading and annotation use cases while maintaining software reliability. Applies SQL performance tuning, caching, and debugging practices to deliver accurate and efficient evaluation infrastructure. • Developed internal dashboards and evaluation tools for AI model assessment workflows • Built scalable backend services and data pipelines for grading and annotation systems • Implemented caching and optimized data processing performance using SQL databases and asynchronous workflows • Delivered evaluation software through technical reasoning, debugging, and structured analysis

2024 - Present

Full-Stack Software Engineer, Outlier AI (AI evaluation & grading/annotation tooling)

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Developed and supported AI model assessment workflows involving evaluation, structured analysis, and contribution to training/validation efforts. Built grading and annotation-oriented backend services and data pipelines to support label generation and quality measurement. Worked on debugging and performance optimization for software evaluation components used in model assessment pipelines. • Created internal dashboards and evaluation tools for AI model assessment workflows • Implemented backend services and data pipelines for grading and annotation systems • Optimized data processing performance using SQL databases and asynchronous workflows • Contributed to AI training and validation projects emphasizing technical accuracy

2024 - Present

Software Engineer, Scale AI (AI training and evaluation systems)

Scale AIText

Engineered infrastructure and processing pipelines for large-scale AI data systems used in training infrastructure and evaluation initiatives. Supported software evaluation workflows and collaborated on system optimization and reliability for model training and validation activities. Focused on distributed processing and efficiency improvements for AI data handling. • Built backend services and processing pipelines for large-scale AI data systems • Optimized workflows for distributed processing and improved system efficiency • Supported AI model training infrastructure and software evaluation initiatives • Collaborated with technical teams on debugging and infrastructure reliability

2023 - 2024

Machine Learning Engineer, IBM (production ML & pipeline evaluation support)

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Developed and deployed NLP and machine learning applications in production, including APIs and scalable services for model serving and real-time processing. Improved reliability and performance of AI pipelines through testing and optimization, using structured datasets and analytics workflows. Contributed to cloud-based deployment systems supporting ongoing model validation and processing. • Built APIs and scalable services for model serving and real-time processing • Worked with structured datasets and analytics workflows • Improved reliability and performance via testing and optimization • Supported cloud-based deployment for production ML pipelines

2022 - 2023

Education

Work History