Description
Summary We are looking for an experienced AI/ML Engineer to perform a thorough code audit of our existing artificial intelligence and machine learning codebase. This is a task-based project. We need someone who can review, assess, and provide actionable technical feedback on our current implementation. What you will be doing: • Review the existing AI/ML codebase for structure, efficiency, and best practices • Identify issues related to model architecture, training workflows, and data processing logic • Assess LLM integration quality, including prompt design, API usage, error handling, and cost efficiency • Evaluate code readability, modularity, scalability, and maintainability • Identify performance bottlenecks, memory concerns, and potential scaling challenges • Review security considerations related to API usage, data handling, and model deployment • Provide a structured audit report with findings, priorities, and recommended improvements You are the right fit if you: • Have hands-on experience building and deploying AI/ML systems • Can quickly understand and analyze complex Python-based AI projects • Have experience with LLMs, NLP systems, or machine learning workflows • Understand software engineering best practices for production AI systems • Can communicate technical findings clearly through detailed documentation Deliverable: A structured AI/ML audit report containing: • Identified issues categorized by severity • Technical explanations of findings • Recommended solutions and improvements • Suggestions for better performance, reliability, and maintainability Please share relevant experience with AI/ML projects or similar technical reviews.