Computer Vision Engineer

3 days ago

Thiruvananthapuram, Kerala, India Vision Logix Full time ₹ 15,00,000 - ₹ 25,00,000 per year

Company Description

Vision Logix is an innovative software development company specializing in
Computer Vision (CV)
solutions. We empower businesses across various industries to unlock the vast intelligence hidden within their visual data—images, videos, and real-time streams—and transform it into actionable insights and automated processes.

Role Description

We are looking for a skilled and passionate Computer Vision Engineer with 2+ years of professional experience to join our team. You will be responsible for designing, developing, and deploying robust computer vision and deep learning models for our products. This role is ideal for an engineer who is ready to take ownership of projects and contribute directly to production-ready systems.

Qualifications

  • Experience:
     
    2+ years of professional experience
     working as a Computer Vision Engineer or Machine Learning Engineer with a focus on computer vision.
  • Education:
     Bachelor's or Master's degree in Computer Science, Electrical Engineering, or a related quantitative field, or equivalent practical experience.
  • Programming Expertise:
     Strong proficiency in 
    Python
     and extensive experience with core computer vision libraries, primarily 
    OpenCV
    .
  • Deep Learning Frameworks:
     Hands-on experience with at least one major deep learning framework: 
    PyTorch
     (preferred) or 
    TensorFlow/Keras
    .
  • Model Development:
     Proven experience developing, training, fine-tuning, and evaluating state-of-the-art computer vision models for real-world applications.
  • Maturity:
     Experience taking a model from the research/prototype phase through to a production environment.

Bonus Considerations

  • Experience with 
    MLOps
     principles and tools for automated model deployment, scaling, and monitoring.
  • Knowledge of 
    containerization technologies
     such as 
    Docker
     and orchestration tools like 
    Kubernetes
    .
  • Experience optimizing models for specific platforms, such as 
    TensorRT
    , 
    ONNX
    , or mobile/edge frameworks.
  • Experience utilizing cloud computing platforms (e.g., AWS, Azure, GCP) for model training and deployment.
  • Strong understanding of performance metrics beyond simple accuracy, such as mAP, IoU, recall/precision trade-offs, and inference time.

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