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Freelance Computer Vision Deep Learning Engineer Jobs in Boston, MA

Senior Machine Learning Engineer

Boston, MA · On-site +1

$161K - $246K/yr

This role centers on leading the design and delivery of advanced computer vision and perception ... We are looking for a seasoned engineer who brings deep technical expertise, sound engineering ...

The ASUS Robotics & AI Center is seeking a Senior Computer Vision Engineer to join our global ... deep learning models using frameworks such asPyTorchor TensorFlow. Working Conditions: * Typically ...

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Freelance Computer Vision Deep Learning Engineer information

See Boston, MA salary details

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$143

How much do freelance computer vision deep learning engineer jobs pay per hour?

As of Aug 25, 2026, the average hourly pay for freelance computer vision deep learning engineer in Boston, MA is $51.83, according to ZipRecruiter salary data. Most workers in this role earn between $26.39 and $67.12 per hour, depending on experience, location, and employer.

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Computer Vision / Machine Learning Engineer

AIToolboard

Boston, MA • On-site

$82.66 - $123.98/hr

Other

Posted 20 days ago


Job description

Jobs / Computer Vision / Machine Learning Engineer

Computer Vision / Machine Learning Engineer

Contractor

About the Role

Computer Vision / Machine Learning Engineer (Contract)Contract Length: 6 monthsWork Arrangement: Hybrid (onsite 3 days/week in Greater Boston)Computer Vision / Machine Learning Engineer to support an active, production-focused initiative. This role is centered on improving detection and tracking accuracy for object-counting systems operating in real-world, high-throughput environments.The ideal candidate has hands-on experience building and deploying computer vision models, working with multimodal sensor data, and optimizing inference pipelines for edge deployment.

What You’ll Work On
  • Enhancing object detection, segmentation, and tracking accuracy in operational systems
  • Developing and deploying models into validation and pre-production environments
  • Improving real-time performance and reliability on edge hardware
Key Responsibilities
  • Model Development: Train, validate, and deploy computer vision models, with an emphasis on instance segmentation
  • Tracking & Fusion: Implement tracking approaches that combine color and depth data to maintain object persistence across frames
  • Data Quality: Support data curation efforts and audit external annotations to ensure high-quality ground truth
  • Performance Optimization: Tune inference pipelines for low-latency execution on edge platforms
Technical Environment
  • Computer Vision & ML: Instance Segmentation, Object Tracking
  • Sensor Data: RGB + Depth (basic multi-sensor fusion)
  • Edge & Optimization: NVIDIA-based edge hardware, TensorRT or similar acceleration tools
Qualifications
  • Proven experience delivering production-grade ML or CV systems
  • Strong software engineering fundamentals (version control, testing, CI/CD)
  • Experience deploying models beyond experimentation into real environments
  • Ability to meet strict accuracy and performance benchmarks
  • Comfortable working within cloud-only data environments with controlled access policies
Nice to Have
  • Experience optimizing models for edge or embedded systems
  • Familiarity with real-time or near–real-time vision pipelines
  • Background in industrial, robotics, or high-volume operational settings
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