Computer Vision Engineer / Cloud Engineer

Role overview

This position is a full-time remote opportunity for a Computer Vision Engineer / Cloud Engineer. The work centers on creating, deploying, and supporting computer vision solutions for industrial and energy-industry scenarios such as image and video analytics, anomaly or pattern recognition, and automated inspection workflows.

What you'll do

You will design and run cloud-native systems that handle data ingestion, model development, inference, monitoring, and scaling using modern cloud services and DevOps methods. The role also calls for close collaboration with cross-functional partners to define requirements, build and test algorithms, connect solutions to existing platforms, and improve both reliability and performance.

In addition, you will prepare technical documentation, follow secure coding and cloud governance standards, and help raise the quality of engineering practices and internal tooling over time.

Required background

The role expects a solid grounding in computer science and data science, including algorithms, data structures, statistics, and machine learning basics. Strong practical knowledge of computer vision and pattern recognition is needed, covering image processing, feature extraction, deep learning-based vision models, and model validation.

Experience or interest in robotics and automation is valuable, especially in areas like perception, sensor integration, or real-time decision-making. You should also be comfortable building and deploying solutions on cloud platforms such as AWS, Azure, or GCP, with working knowledge of Docker, Kubernetes, and CI/CD pipelines.

Programming ability in languages commonly used for vision and cloud engineering, such as Python, C++, or Java, along with frameworks like OpenCV, TensorFlow, or PyTorch, is important. A bachelor’s degree or higher in Computer Science, Electrical/Computer Engineering, Data Science, or a similar technical discipline, or equivalent hands-on experience, is expected.

Additional strengths

Success in this role also depends on strong problem-solving ability, the capacity to work independently in a remote environment, and clear communication with both technical and non-technical stakeholders. Experience in industrial, energy, or other asset-heavy environments is a plus, and familiarity with MLOps, edge deployment, or real-time streaming systems will be beneficial.