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Computer Vision Machine Learning Jobs in Massachusetts

Eka

Machine Learning / Computer Vision Engineer

Boston, MA · On-site

$90 - $130/hr

Strong background in machine learning for computer vision, especially deep learning‑based visual perception. * Experience training modern computer vision models in JAX, PyTorch or similar ...

Axon

Senior Machine Learning Scientist

Boston, MA · On-site

$99K - $135K/yr

Your Impact We are seeking highly skilled and innovative Machine Learning Scientists to join our AI team, focusing on AI applications (LLM and Computer Vision) in Cloud, Devices and Robotics. As a ...

Axon

Senior Machine Learning Scientist

Boston, MA · On-site

$99K - $135K/yr

Your Impact We are seeking highly skilled and innovative Machine Learning Scientists to join our AI team, focusing on AI applications (LLM and Computer Vision) in Cloud, Devices and Robotics. As a ...

Axon

Senior Machine Learning Scientist

Boston, MA · On-site

$99K - $135K/yr

Research and develop cutting-edge techniques in LLM, MLLMs, GenAI, and Computer Vision across cloud ... in computer vision, machine learning, and deep learning, MLLMs, GenAI and integrate relevant ...

Motion Recruitment

Lead Robotics Perception Engineer

Boston, MA · On-site

$111K - $147K/yr

MS or PhD in Computer Science, Robotics, Computer Vision, Machine Learning, or related discipline * Experience working with ROS2 or comparable robotics middleware * Experience deploying AI models on ...

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How much do computer vision machine learning jobs pay per hour?

As of Aug 21, 2026, the average hourly pay for computer vision machine learning in Massachusetts is $21.75, according to ZipRecruiter salary data. Most workers in this role earn between $17.84 and $23.89 per hour, depending on experience, location, and employer.

What is a computer vision machine learning engineer?

A Computer Vision Machine Learning Engineer is a professional who develops algorithms and models that enable computers to interpret and understand visual data from the world, such as images and videos. They use techniques from machine learning, deep learning, and image processing to build systems capable of tasks like object detection, image classification, facial recognition, and scene understanding. Their work is critical in fields such as autonomous vehicles, healthcare imaging, security, and augmented reality. These engineers typically have strong skills in programming, mathematics, and data analysis, and often work closely with data scientists and software developers.

What are the key skills and qualifications needed to thrive as a computer vision machine learning engineer?

To thrive as a Computer Vision Machine Learning Engineer, you need strong foundations in mathematics, programming (especially Python or C++), and expertise in machine learning algorithms, typically supported by a degree in computer science, engineering, or a related field. Familiarity with deep learning frameworks like TensorFlow or PyTorch and experience with image processing libraries are essential, along with knowledge of version control systems. Strong problem-solving, collaboration, and communication skills help you translate complex requirements into effective models and work efficiently in multidisciplinary teams. These skills ensure the development of robust computer vision solutions that address real-world challenges and drive innovation.

What are some common challenges faced by computer vision machine learning engineers when deploying models to production environments?

Computer Vision Machine Learning engineers often encounter challenges such as ensuring models perform well on real-world, diverse image data that may differ from training datasets. Managing computational efficiency and latency is crucial, especially for real-time applications. Additionally, integrating models with existing software systems and maintaining accuracy as data evolves can be complex. Collaboration with data engineers, software developers, and product teams is essential to address these challenges and ensure smooth deployment and monitoring.

What is the difference between Computer Vision Machine Learning vs Data Scientist?

AspectComputer Vision Machine LearningData Scientist
Required CredentialsBachelor's or higher in CS, ML, or related; experience with ML frameworksBachelor's or higher in CS, Statistics, or related; strong analytical skills
Work EnvironmentResearch labs, tech companies, AI startups focusing on visual dataBusiness, finance, healthcare sectors analyzing diverse data sets
Industry UsageDeveloping visual recognition systems, image processingData analysis, predictive modeling, business insights
Common Search/ComparisonYesYes

While both roles involve machine learning, Computer Vision Machine Learning specializes in visual data and image processing, whereas Data Scientists work with a broader range of data types to generate insights across various industries.

Is machine learning used in computer vision?

Yes, machine learning is fundamental to computer vision, enabling systems to interpret and analyze visual data such as images and videos. Computer vision professionals often use techniques like deep learning and neural networks to develop applications like object detection, facial recognition, and image classification.

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

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

What job categories do people searching Computer Vision Machine Learning jobs in Massachusetts look for?

The top searched job categories for Computer Vision Machine Learning jobs in Massachusetts are:

What cities in Massachusetts are hiring for Computer Vision Machine Learning jobs?

Cities in Massachusetts with the most Computer Vision Machine Learning job openings:

Computer Vision Machine Learning jobs near you
Infographic showing various Computer Vision Machine Learning job openings in Massachusetts as of August 2026, with employment types broken down into 1% As Needed, 81% Full Time, 13% Part Time, and 5% Contract. Highlights an 96% Physical, 1% Hybrid, and 3% Remote job distribution, with an average salary of $45,245 per year, or $21.8 per hour.

Computer Vision / Machine Learning Engineer

AIToolboard

Boston, MA • On-site

$82.66 - $123.98/hr

Other

Posted 15 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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