Machine Learning Engineer - Computer Vision

The Role

Nuage has partnered with a scale-up to recruit an ML Engineer with a strong focus on Computer Vision. In this role, you will be instrumental in building and maintaining the infrastructure that supports machine learning models at scale, particularly those involving Computer Vision. This is a unique opportunity to contribute to transformative technology that will drive the company's growth and innovation.

Responsibilities

• Design, implement, and maintain scalable ML infrastructure with a focus on computer vision applications.
• Automate the deployment and monitoring of computer vision models.
• Ensure the reliability and performance of computer vision systems in production.
• Collaborate with data scientists and engineers to integrate computer vision models into applications.
• Develop and maintain CI/CD pipelines for computer vision projects.
• Monitor and troubleshoot production computer vision systems.
• Optimize resource usage and cost-efficiency of computer vision infrastructure.
• Stay updated with advancements in ML Ops, computer vision, and cloud technologies.
• Document processes and best practices.
• Provide training and support to team members on ML Ops tools and practices, with an emphasis on computer vision.

Your Background

• Bachelor’s or Master’s degree in Computer Science, Data Engineering, Machine Learning, or a related field.
• 4-5 years of experience in ML Ops or related roles, with a focus on computer vision.
• Experience with cloud platforms (e.g., AWS, GCP, Azure) and containerization (e.g., Docker, Kubernetes).
• Proficiency in scripting and automation (e.g., Python, Bash).
• Strong understanding of the ML lifecycle and deployment strategies, particularly for computer vision models.
• Experience with monitoring and logging tools (e.g., Prometheus, Grafana).
• Familiarity with computer vision frameworks (e.g., OpenCV, TensorFlow, PyTorch).
• Experience with infrastructure as code (e.g., Terraform, Ansible).
• Strong software engineering skills, including version control (Git) and collaborative workflows.
• Prior experience working in a collaborative, fast-paced team.