Computer Vision & ML Expert, AI

G2i Inc.; United States; Remote; CAD 56,520 - 131,881; Part time

Job summary

G2i Inc. is seeking independent contractors to evaluate and train AI models related to computer vision. The role is fully remote and focuses on tasks such as assessing AI outputs and refining training data. Applicants should have strong knowledge of computer vision and hands-on experience with deep learning frameworks like PyTorch and TensorFlow. Compensation ranges from $30 to $70 per hour depending on location and experience, with flexible hours available.

Qualifications

• Strong foundational knowledge of computer vision including object detection and image classification.
• Hands-on experience with deep learning frameworks.
• Clear and concise written communication skills.

Responsibilities

• Evaluate AI-generated outputs on visual tasks.
• Assess model predictions for quality and accuracy.
• Create and refine training data annotations.

Skills

Computer vision knowledge

Experience with deep learning frameworks

Understanding of CV architectures

Clarity in written communication

Self-motivation

Education

MS or PhD in Computer Science or related field

Tools

PyTorch

TensorFlow

Python

Job description

Overview

This role is open to contractors in accepted locations only. Please confirm your country is on the list before applying — we\'re unable to process applications from unlisted locations. List of accepted countries and locations.

For US applicants

This is a 1099 independent contractor role. It is not compatible with F-1 OPT, STEM OPT, or any visa status that requires W-2 employment, guaranteed hours, or employer sponsorship.

We are unable to provide offer letters or employment verification for this role.

What You\'ll Be Doing

Help train and evaluate AI models that perceive, interpret, and understand the visual world — from image recognition and object detection to segmentation and visual reasoning:

• Evaluate AI-generated outputs on image recognition, object detection, segmentation, and visual reasoning tasks
• Assess the quality, accuracy, and robustness of computer vision model predictions
• Identify failure modes, edge cases, and biases in visual AI systems
• Create, review, and refine training data annotations for CV pipelines
• Write detailed technical evaluations and suggest concrete improvements

End result: the model learns to see, interpret, and reason about visual data the way a trained expert would.

RLHF in one line: Generate code → expert engineers rank, edit, and justify → convert that feedback into reward signals → reinforcement learning tunes the model toward code you\'d actually ship.

What You\'ll Need

• Strong foundational knowledge of computer vision — object detection, image classification, semantic segmentation, pose estimation, or related areas
• Hands-on experience with deep learning frameworks such as PyTorch, TensorFlow, or JAX
• Familiarity with common CV architectures (CNNs, Vision Transformers, diffusion models, etc.)
• Comfortable reading and understanding ML research papers
• Solid understanding of data preprocessing, augmentation, and annotation best practices for visual data
• Detail-oriented and systematic in evaluating model outputs
• Clear, concise written communicator who can explain technical concepts effectively in English
• Self-motivated and reliable when working independently

Identity verification: Applicants will be required to verify their identity and confirm they have valid documentation to work as an independent contractor in their country of residence.

Nice to Have

• MS or PhD in Computer Science, Electrical Engineering, or a related field with a focus on CV or ML
• Published research in top CV/ML venues (CVPR, ICCV, ECCV, NeurIPS, ICML, etc.)
• Experience with 3D vision, video understanding, generative models, or multimodal AI
• Familiarity with MLOps tools, experiment tracking, and model evaluation pipelines
• Background in specialized domains such as medical imaging, remote sensing, robotics, or autonomous driving
• Experience with annotation platforms and data quality workflows at scale
• Proficiency in Python and scientific computing libraries (NumPy, OpenCV, scikit-learn)

What You Don\'t Need

• No prior RLHF or AI training experience

Logistics

• Location: Fully remote — work from anywhere on the accepted locations list
• Compensation: $30–$70/hr based on location and seniority. Note: the majority of projects run at around $30/hr — higher rates apply to senior profiles and specific project types
• Hours: Minimum 15 hrs/week, up to 40+ hrs/week available — hours vary by project and are not guaranteed week to week
• Payment: Weekly via PayPal or Stripe

Important: Hours are project-dependent and can vary week to week. We recommend keeping other work options open alongside this engagement rather than relying on it as your sole source of income.