Computer Vision Researcher

overview

We are looking for an experienced computer vision researcher to lead the development of AI models for the energy sector.

Responsibilities:

  • As an Engineering Leader, you're responsible for developing the concepts of new products while supporting the growth of current products

  • You will help define our growth strategy while working with Product Managers and cross-functional teams to align the strategy, process, and execution of the product roadmap

  • You will play an active part in measuring and overseeing the quality and experience of the product while maintaining agility

  • Push the state-of-the-art on standard computer vision tasks for understanding documents across the energy sector

  • Develop the infrastructure for training and deploying models, including massive data pipelines, experiment management platforms, visualization tools

  • Improve runtime efficiency of models for deployment

  • Own data assets and annotation efforts

requirements

  • Master's degree in computer science, artificial intelligence, machine learning, or a related technical field.

  • 2+ years of experience in computer vision research and applications.

  • Research background in Computer Vision, Deep Learning, Machine Learning, or related field(s).

  • Experience in theoretical and empirical research and in addressing research problems.

  • Experience in deep learning frameworks such as PyTorch or TensorFlow.

  • Experience developing and debugging in Python.

  • Experience with OpenCV or similar.

extra credit

  • Experience with OCR research and production systems for enterprise applications

  • Proven track record of achieving significant results as demonstrated by grants, fellowships, patents, or first-authored publications at conferences such as CVPR, ECCV, ICCV, ICML, NeurIPS, SIGGRAPH, or similar.

  • Experience solving complex problems and comparing alternative solutions, tradeoffs, and diverse points of view to determine a path forward.

  • Experience working and communicating cross functionally in a team environment.

additional information

  • Hybrid - In-office (Tue, Wed, Thur), Flex (Mon, Fri)

  • Paris, NYC, Calgary

  • Compensation commensurate with experience