OpenTrain is the #1 platform for building careers in AI training and data labeling. Contributors on OpenTrain play a direct role in shaping how modern AI systems behave by reviewing and improving model outputs, code, and documentation.
This role is contracted and managed by OpenTrain AI. You will join a growing community of experts who help train and evaluate AI through structured reviews, feedback, and annotation work.
About AI training and data-labeling work
AI training (also called data labeling, annotation, or human feedback work) is the human side of building AI systems. Experts review model outputs, validate code and recommendations, and provide the contextual judgement machines still need.
These projects are often 100% remote, flexible, and accessible — many let you set hours and workload. Experienced practitioners are especially valued on technical projects like model code review and deployment assessment.
The role
You will act as an AI interviewer and technical reviewer focused on YOLOv7 and object-detection workflows. Your primary job is to assess AI-generated prompts, explanations, and code snippets for technical accuracy, efficiency, and real-world applicability.
Work is contract, part-time (under 20 hours per week), paid hourly at $30 USD. This is a remote, worldwide role; clear, professional English writing is required for structured feedback and interview notes.
Assess AI-generated YOLOv7 code, explanations, and deployment recommendations for correctness and best practices.
Conduct structured interviews that probe candidates’ YOLOv7 experience, problem-solving, and code-review skills.
Provide clear, actionable written feedback to improve AI responses and candidate outputs.
What you'll do
Evaluate AI-generated content and code related to YOLOv7, verifying correctness, performance claims, and deployment feasibility. Identify bugs, inefficiencies, missing context, or risky recommendations and propose concrete fixes.
Run through interview flows: greet candidates, explain the process, ask technical QA questions (training, architecture, inference acceleration), present code snippets and AI responses for critique, and request improved rewrites where appropriate.
Verify code correctness for PyTorch YOLOv7 training and inference snippets.
Assess model evaluation metrics (mAP, IoU, FPS) claims and advise on measurement methodology.
Evaluate deployment guidance for edge runtimes (TensorRT, ONNX, OpenVINO) and quantization trade-offs.
Provide concise, structured code-review comments and improved AI response rewrites.
Requirements
You must have deep, hands-on experience with YOLOv7 and object detection. The role description requires at least 5+ years of practical experience in object detection, deep learning, and real-time computer vision applications.
Strong technical skills and communication are mandatory because you will both evaluate low-level code and produce clear written feedback that non-expert reviewers can act on.
Minimum 5+ years hands-on experience in object detection and real-time computer vision.
Expertise training, fine-tuning, and optimizing YOLOv7 models, including dataset preprocessing and anchor box tuning.
Experience with PyTorch, image augmentation techniques, model evaluation (mAP, IoU, FPS), and inference acceleration.
Knowledge of model quantization and deployment on edge devices using TensorRT, ONNX, or OpenVINO.
Excellent English writing skills for structured, professional feedback and interview facilitation.
Prior code-review, debugging, or documentation experience is a strong plus.
Who should apply
Experienced ML engineers and computer-vision specialists who have shipped or extensively worked with YOLOv7 and edge deployment are a great fit. If you enjoy diagnosing model/code issues and explaining improvements clearly, you’ll thrive in this role.
This is not a purely annotation task: you will be judged on technical depth, ability to spot subtle issues, and the quality of your written guidance.
OpenTrain AI seeks an experienced PyTorch developer to review AI-generated YOLO code, prompts, and model recommendations; part-time contractor work (<20 hrs/week) at $25/hr, remote and worldwide. Provide technical feedback, code reviews, and improved responses aligned with best practices.
OpenTrain is hiring an expert C++ engineer to review AI-generated C++ code, produce reference implementations, and write clear step-by-step technical explanations. Contractor role: $65/hour, 20+ hours/week, remote in the countries listed below.
Review AI-generated Angular code, assess correctness and best practices, and provide clear written feedback to improve model outputs. Part-time contractor role, $25/hr, remote worldwide, under 20 hours/week.
