AI Coding Rater

GDM Coding - Freelance (20 to 40 hours a week) Job Description: Responsibilities: • Model Quality Assessment: Evaluate the quality of AI model responses that include code, machine learning, AI, identifying errors, inefficiencies, and non-compliance with established standards. • Code Annotation and Labeling: Accurately generate, annotate and label code snippets, algorithms, and technical documentation according to project-specific guidelines. • Review and Feedback: Provide detailed, constructive feedback on model and other outputs • Comparative Analysis: Compare multiple outputs and rank them based on criteria such as correctness, efficiency, readability, and adherence to programming best practices. • Data Validation: Validate and correct datasets to ensure high-quality data for model training and evaluation. • Collaboration: Work closely with data scientists and engineers to identify new annotation guidelines, resolve ambiguities, and contribute to the overall project strategy. Qualifications: • Strong background in software engineering/development, computer science, ML/AI, or related technical field, with a keen eye for detail and a passion for data accuracy • Programming Proficiency: Demonstrated expertise in: • Python (must-have) and at least one or more common programming languages such as: JavaScript, Rust, Node.js, Typescript, C, C++, Shell • (Bonus points) At least 1 or more less common programming languages such as: Rust, Shell, Go, Ruby, Swift, PHP, Kotlin • Knowledge of web technologies & frameworks • Web Scraping, API integration, • HTML/CSS/JavaScript • Web application development (e.g. Flask) • Frontend (e.g. React) and backend (e.g. Node.js) development • Machine Learning & Artificial Intelligence • Machine Learning (General concepts, model development, experimentation, training, evaluation) • Deep Learning (General, frameworks like TensorFlow, PyTorch, JAX, Keras, neural networks, CNNs, RNNs, transformer architecture, LSTM) • Natural Language Processing (NLP) • Reinforcement Learning (e.g., PPO, Q-learning, policy gradients, A2C, DQN, AlphaZero) • Computer Vision (e.g., image processing, analysis, instance segmentation, OCR, deepfake detection)