Computer Vision Engineer - Hybrid

CyberCoders South Boston, MA $165,000 per year Fulltime

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Summary

Hybrid work with 3 days onsite weekly; develops, trains, optimizes, and deploys computer vision models for real-world environments. Requires 2+ years’ experience, Python, a bachelor’s degree, and U.S. work authorization without sponsorship.

Highlights

Work Arrangement
Hybrid
Schedule
3 days onsite weekly
Experience
2+ years hands-on computer vision and ML experience
Education
Bachelor's degree required; Master's or PhD preferred
Type
Full-Time

Job description

AI/ML Engineer - Computer Vision

Computer Vision Engineer

Hybrid | Greater Boston Area | 3 Days Onsite Weekly
Full-Time

About the Opportunity

We are a venture-backed technology company building AI-powered solutions that bring real-time intelligence to complex operational environments. Our team is leveraging machine learning and computer vision to solve challenging real-world problems at scale.

We are seeking a Computer Vision Engineer to join our growing team. In this role, you will develop, train, optimize, and deploy computer vision models that operate in real-world environments. You will work across the full machine learning lifecycle, from experimentation and model development through deployment and production support.

This is an excellent opportunity for an engineer who enjoys taking ownership, solving challenging computer vision problems, and seeing their work deployed in real-world environments.

Responsibilities

  • Design, train, fine-tune, and deploy machine learning and computer vision models for production applications
  • Develop solutions involving object detection, segmentation, image classification, tracking, anomaly detection, and image processing
  • Conduct experimentation and prototyping to improve model accuracy, performance, and reliability
  • Optimize computer vision models for real-time inference and production deployment
  • Build and maintain pipelines supporting data preparation, model training, evaluation, and deployment
  • Analyze model performance and failure cases and continuously improve deployed systems
  • Collaborate with software engineers, product teams, customers, and domain experts to solve complex technical challenges
  • Troubleshoot, debug, and optimize machine learning systems operating in real-world environments
  • Stay current with emerging computer vision and machine learning models, techniques, and technologies

Qualifications

  • 2+ years of hands-on experience developing computer vision and machine learning systems
  • Strong programming skills in Python
  • Recent hands-on experience training or fine-tuning computer vision models for object detection, segmentation, classification, or tracking
  • Experience with frameworks and libraries such as PyTorch, YOLO, TensorFlow, OpenCV, scikit-learn, or similar technologies
  • Experience with image processing and both traditional and deep learning-based computer vision techniques
  • Understanding of supervised, unsupervised, and semi-supervised learning methods
  • Experience evaluating and optimizing model accuracy, latency, and overall performance
  • Strong debugging, optimization, and problem-solving skills
  • Experience with Git and modern software development practices
  • Bachelor's degree in Computer Science, Engineering, Machine Learning, Data Science, or a related technical field

Preferred Qualifications

  • Master's degree or PhD in a related technical field
  • Experience deploying computer vision or machine learning models into production
  • Experience developing computer vision systems for manufacturing, machine vision, quality inspection, robotics, or industrial automation
  • Experience with edge computing, embedded inference, or real-time computer vision systems
  • Familiarity with anomaly detection, autoencoders, or traditional computer vision techniques
  • Experience working directly with customers or end users to translate real-world problems into technical solutions
  • Startup or fast-paced product development experience

What We Offer

  • Competitive compensation and equity package
  • Opportunity to work on challenging, real-world computer vision problems
  • High-impact role with significant ownership and visibility
  • Collaborative and mission-driven engineering culture
  • Hybrid work environment in the Greater Boston area
  • Opportunity to help shape the technical direction of a rapidly growing company
- For this position, you must be currently authorized to work in the United States without the need for sponsorship for a non-immigrant visa. This job was first posted by CyberCoders on 09/08/2026 and applications will be accepted on an ongoing basis until the position is filled or closed.Everforth CyberCoders is proud to be an Equal Opportunity Employer

All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, age, sexual orientation, gender identity or expression, national origin, ancestry, citizenship, genetic information, registered domestic partner status, marital status, status as a crime victim, disability, protected veteran status, or any other characteristic protected by law. Our hiring process includes AI screening for keywords and minimum qualifications, and a virtual recruiter as part of the application process. A human recruiter reviews all results. Click here for details on our virtual recruiter .  Everforth CyberCoders will consider qualified applicants with criminal histories in a manner consistent with the requirements of applicable state and local law, including but not limited to the Los Angeles County Fair Chance Ordinance, the San Francisco Fair Chance Ordinance, and the California Fair Chance Act. Everforth CyberCoders is committed to working with and providing reasonable accommodation to individuals with physical and mental disabilities. Individuals needing special assistance or an accommodation while seeking employment can contact a member of our Human Resources team at Benefits@CyberCoders.com to make arrangements.

Salary

$120000 - $165000 USD per year

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