We are sharing a specialised part-time consulting opportunity for computer vision professionals experienced in visual recognition, detection, segmentation, multimodal reasoning, image and video generation, Python development, and advanced model evaluation.
This role supports a remote collaboration focused on improving how advanced AI systems interpret, reason about, and generate visual information. Selected professionals will apply their computer vision expertise to design realistic technical tasks, develop rigorous reference solutions, evaluate model performance, identify capability gaps, and contribute to high-quality vision assessment workflows.
Key Responsibilities
Computer Vision Task Development
- Design challenging, real-world computer vision problems based on applied industry, research, or open-source experience
- Develop tasks involving object detection, segmentation, recognition, tracking, multimodal reasoning, and vision-language systems
- Create image and video generation challenges targeting specific technical capabilities
- Calibrate task difficulty, expected behavior, and evaluation criteria against modern computer vision standards
Reference Solution & Evaluation Environment Creation
- Build clear specifications, reference solutions, and supporting technical materials
- Prepare executable tests and validation workflows using Python where applicable
- Integrate tasks into structured development and evaluation environments
- Review reference implementations for correctness, reproducibility, and technical quality
Model Performance Evaluation
- Evaluate advanced model outputs across visual understanding, reasoning, generation, and agentic workflows
- Assess outputs for correctness, robustness, consistency, and alignment with task requirements
- Identify failure cases involving perception, localization, classification, spatial reasoning, or multimodal interpretation
- Document evaluation decisions clearly and support findings with technical evidence
Capability Gap Analysis
- Identify tasks where meaningful performance headroom remains
- Classify model failures according to their technical cause and severity
- Distinguish between reasoning errors, implementation issues, perception failures, and evaluation limitations
- Collaborate with other subject-matter experts to maintain consistent and accurate assessment standards
Ideal Profile
Strong candidates may have:
- Deep hands-on experience in computer vision through industry work, academic research, graduate study, or open-source contributions
- Practical proficiency in Python used in research, production, or technical development environments
- Strong understanding of modern computer vision methods, deep learning architectures, and evaluation practices
- Experience with object detection, segmentation, recognition, vision-language systems, or generative vision models
- Ability to design technically rigorous tasks and analyze model behavior independently
- Strong written communication and time-management skills
- Availability to contribute approximately 20 hours per week
- Current location in the United States
Educational Background
- A degree in computer science, electrical engineering, computer engineering, applied mathematics, robotics, or a related technical field is helpful
- Graduate-level research or doctoral training in computer vision, machine learning, artificial intelligence, or a related discipline is highly relevant
- Professional experience developing or evaluating production computer vision systems is also highly valuable
- Equivalent hands-on experience through established open-source or research contributions may be considered
Nice to Have
- Experience with PyTorch, TensorFlow, OpenCV, or comparable computer vision frameworks
- Familiarity with vision transformers, convolutional architectures, diffusion models, or multimodal foundation models
- Experience building datasets, evaluation benchmarks, test harnesses, or reproducible research pipelines
- Knowledge of standard computer vision metrics and error-analysis methodologies
- Experience with image or video generation, visual question answering, or agent-based vision systems
- Previous involvement in AI training, model evaluation, technical benchmarking, or structured data review
- Open-source contributions related to computer vision, machine learning, or evaluation tooling
Why This Opportunity
- Apply advanced computer vision expertise to structured remote work
- Contribute to the development of stronger visual reasoning and multimodal evaluation systems
- Design realistic tasks aligned with your technical specialization and practical experience
- Use your ability to identify subtle model failures and assess complex visual outputs
- Participate in flexible, high-impact technical work with competitive hourly compensation
Contract Details
- Part-time W-2 contingent employment arrangement
- Fully remote within the United States
- Expected commitment of approximately 20 hours per week
- Competitive rates between $75–$105 per hour depending on experience, technical depth, and project scope
- Role-based engagement involving collaboration with technical experts and evaluation teams
- Work schedules and engagement details may be adjusted depending on scope, performance, and business needs
- Work will not involve access to confidential or proprietary information from any employer, client, or institution
About the Platform
This opportunity is available through 24-MAG LLC. We connect experienced professionals with remote consulting opportunities across technical, evaluation, and project-based workstreams.
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