Production-Ready Computer Vision Engineer (Hybrid Boston)

CyberCoders; Boston (MA); Hybrid; USD 110,000 - 170,000; Full time

Benefits offered by this job

Equity

Hybrid work

High impact role

Ownership

Collaborative culture

Job summary

CyberCoders in Greater Boston is seeking a Computer Vision Engineer to design, train, optimize, and deploy CV models for real-world environments. You will work across the full ML lifecycle, from experimentation to production support, and collaborate with software engineers, product teams, and customers.

In this hybrid role, you will contribute to real-time CV solutions using PyTorch, TensorFlow, OpenCV, and related tools, with ownership of model performance and deployment outcomes in a

Qualifications

• 2+ years hands-on experience developing CV/ML systems.
• Proficient Python programming and debugging skills.
• Experience training or fine-tuning CV models (detection/segmentation/classification/tracking).
• Experience with PyTorch, TensorFlow, OpenCV or similar libraries.

Responsibilities

• Design, train, fine-tune, and deploy CV models for production apps.
• Develop solutions for object detection, segmentation, classification, tracking.
• Prototype to improve model accuracy, latency, and reliability.
• Optimize CV models for real-time inference and deployment.
• Build data pipelines for prep, training, evaluation, and deployment.
• Analyze performance and failure cases to improve systems.
• Collaborate with software engineers, product teams, and customers.

Skills

Python

Computer Vision

Model Training

Debugging

Education

Bachelor's degree in CS/Engineering/ML

Tools

PyTorch

YOLO

TensorFlow

OpenCV

scikit-learn

Job description

CyberCoders in Greater Boston is seeking a Computer Vision Engineer to design, train, optimize, and deploy CV models for real-world environments. You will work across the full ML lifecycle, from experimentation to production support, and collaborate with software engineers, product teams, and customers.

In this hybrid role, you will contribute to real-time CV solutions using PyTorch, TensorFlow, OpenCV, and related tools, with ownership of model performance and deployment outcomes in a