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Machine Learning Engineer

Bossa Nova Robotics

Bossa Nova Robotics

Software Engineering
Pittsburgh, PA, USA
Posted on Wednesday, July 27, 2022

About Bossa Nova

Bossa Nova pioneered the automated data capture and analysis of on-shelf inventory since 2013. Our claim to fame is the deployment of robots in 600 Walmart supercenters to create a massive training data set of 134M labeled product images. The resulting Product ID engine is the industry’s best, and works as well on images from mobile devices as from robots and fixed cameras. We mine this data to provide insights to store associates to restock shelves, to product manufacturers to run promotions, and to third parties to fulfill online orders. 

Join us on the journey to become the AI engine of choice for the retail industry. 

Position

Bossa Nova is looking for a skilled Machine Learning Engineer to help us transform the retail industry with our AI technologies.

Bossa Nova is looking for a new graduate to mid-level Machine Learning Engineer specializing in Computer Vision. The ideal candidate will have a passion for developing robust and reliable machine learning models and computer vision applications in the retail space.

Responsibilities

  • Manage the full SDLC for new ML models and applications
  • Scale-up and optimize the performance of existing models for cloud and edge hardware.
  • Write clean, quality code while iterating on AI experiments in Python
  • Define and track metrics for improvements
  • Own and improve on best-practice ML workflows from ideation to deployment.

Qualifications

  • Bachelors, Masters, or PhD Degree in Computer Science/Machine Learning or equivalent professional experience.
  • Strong background in Python development with Linux
  • Experience with Pytorch, Tensorflow, or similar frameworks
  • Experience with end-to-end deep learning application development

Preferred Qualifications

  • Experience with training and deployment workflows in cloud platforms
  • Experience with developing computer vision on low power edge computing
  • Experience with MLOps tools (e.g. MLFlow, Kubeflow, or similar)
  • Experience with large data management, and databases