Computer Vision Engineer

At Hermes Corporate, we have been supporting companies in digital transformation for over 15 years through IT consulting, outsourcing services, and digital talent development.
We are looking for a skilled Computer Vision Engineer to design, develop, and deploy advanced vision-based solutions for real-world applications. You will work on building robust, production-ready AI systems, with the opportunity to engage in robotics-related applications depending on project needs, at the intersection of AI and intelligent systems.

Key Responsibilities

Design, develop, and deploy computer vision models for real-world applications
Build and optimize deep learning models for tasks such as object detection, segmentation, classification, tracking, and pose estimation
Develop scalable image and video processing pipelines for both training and inference
Deploy and optimize models for real-time and edge environments, ensuring low latency and high efficiency
Integrate vision models into production systems and intelligent platforms
Collaborate with cross-functional teams (software, hardware, product) to deliver end-to-end solutions
Evaluate model performance using real-world data and continuously improve accuracy, robustness, and efficiency
Stay up to date with the latest advancements in computer vision, deep learning, and applied AI

Required Qualifications

Bachelor’s degree in Computer Science, Artificial Intelligence, or a related field
2+ years of hands‑on experience in computer vision and deep learning
Strong programming skills in Python

Experience with deep learning frameworks such as PyTorch or Tensor Flow
Solid understanding of core computer vision concepts (image processing, CNNs, feature extraction, object detection)
Experience training and deploying machine learning models in production environments
Familiarity with model optimization techniques (e.g., quantization, pruning, ONNX)
Experience working with image/video datasets and data pipelines
Strong analytical and problem‑solving skills

Preferred Qualifications

Master’s degree in Computer Vision, Machine Learning, or a related field

Experience with real-world or industrial AI applications
Exposure to robotics or autonomous systems (preferred but not mandatory)
Familiarity with edge deployment or performance‑constrained environments

Experience with cloud‑based ML infrastructure and MLOps workflows

Nice to Have

Experience with infrastructure robustness testing to ensure system stability and reliability
Hands‑on experience with real-world system integration and validation
Exposure to field testing and performance evaluation in live environments
Familiarity with end‑to‑end system validation under varying operating conditions

Experience with robotics systems is a plus

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