Founding Computer Vision Engineer

Opus Recruitment Solutions
Slough, England
12 months ago
Applications closed

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Hybrid - London Office


About the Role:


I'm working with a well funded start-up seeking a talented Computer Vision Engineer with a robust software engineering background to join our dynamic Tech Team. Reporting to the Engineering Manager / Head of Data, you will be instrumental in developing production-ready models, scaling AI infrastructure, and enhancing our core vision capabilities.


This role offers a unique opportunity to push the boundaries of AI in practical applications, utilizing cutting-edge Computer Vision, Deep Learning, and MLOps technologies.


Key Responsibilities:

  • Develop and optimize high-performance Computer Vision and deep learning algorithms for real-time monitoring.
  • Implement scalable AI solutions that transition seamlessly from research to production-level software.
  • Manage the entire AI pipeline, including data collection, labeling, processing, and model deployment.
  • Enhance core vision features such as visual weighing, behavior tracking, and health assessment.
  • Optimize model efficiency and inference speed for deployment on edge devices and cloud-based systems.
  • Collaborate with engineers and researchers to improve model accuracy, robustness, and interpretability.
  • Participate in code reviews, debugging, and validation/testing to ensure high-quality, maintainable code.
  • Stay updated with industry trends in AI/ML, deep learning architectures, and MLOps best practices.


About You:

  • 4+ years of hands-on experience developing Computer Vision and Deep Learning models in production environments.
  • Strong software engineering skills, including clean coding, modular design, and best practices.
  • Experience deploying ML models at scale, with knowledge of MLOps, model optimization, and inference acceleration.
  • Proficiency in Python and AI/ML frameworks like PyTorch and TensorFlow.
  • Familiarity with cloud platforms (AWS, GCP, Azure) and containerized environments (Docker, Kubernetes).
  • Ability to communicate complex AI concepts clearly to both technical and non-technical stakeholders.
  • A natural collaborator who enjoys knowledge sharing and supporting team members.



Desirable:

  • Previous experience working with real-time video.
  • Knowledge of camera models and calibration.
  • Start-up or scale-up experience.

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