ZipRecruiter

Log In

1

Computer Vision Machine Learning Research Jobs (NOW HIRING)

next page

Showing results 1-20

All JobsTechnology JobsData JobsData Scientist JobsComputer Vision Machine Learning Research Jobs

Computer Vision Machine Learning Research information

See salary details

$111.5K

$206K

How much do computer vision machine learning research jobs pay per year?

As of Sep 10, 2026, the average yearly pay for computer vision machine learning research in the United States is $200,510.00, according to ZipRecruiter salary data. Most workers in this role earn between $205,000.00 and $205,000.00 per year, depending on experience, location, and employer.

What are popular job titles related to Computer Vision Machine Learning Research jobs?

For Computer Vision Machine Learning Research jobs, the most frequently searched job titles are:

Infographic showing various Computer Vision Machine Learning Research job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 78% Full Time, 15% Part Time, and 6% Contract. Highlights an 94% Physical, 1% Hybrid, and 5% Remote job distribution, with an average salary of $200,510 per year, or $96.4 per hour.

Computer Vision / Machine Learning Engineer

Boston, MA • On-site

AIToolboard
See more jobs at AIToolboardexternal

$121K - $142K/yr

Other

Re-posted 5 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
#J-18808-Ljbffr

Apply