AI Engineer

il y a 7 jours

Paris, Île-de-France Bloomfield Robotics Temps plein

About the Company

Plant level knowledge is vital to satisfying the food production needs from projected a forty percent increase in world population over the next thirty years. We support that goal by continuously and automatically assessing the health and performance of the world's +$1T specialty crops, one plant at a time, with deep learning and imaging. Currently, Bloomfield is focused on wine, table, and juice grapes as well as, more recently, blueberries. Our portable Flash cameras and supporting platform capture, geo-locate and share the condition of each vine, tree and bush, along with the various features of that plant. This information, in turn, informs a variety of decisions and actions that growers take every day to increase the size, quality and consistency of yields and doing so without increasing the resources used to produce those yields.

About the Role

Our rapidly growing engineering team is in search of an AI Engineer to lead the design and development of deep learning models on large amounts of high resolution image data, as well as analytical modeling solutions at scale on a cloud platform.

As an AI Engineer, you will work at start-up speed and can plan and develop roadmaps, adapting along the way to dynamic conditions. You should have a detail-oriented engineering and algorithmic mindset, and enjoy building, instrumenting, testing, and documenting large systems. You will have broad responsibilities, build a team as we grow, and be a part of the senior team. This is a full-time, exempt position that reports to the Head of Product.

Responsibilities

  • Deep model development: develop new image processing models that include feature detection and instance segmentation.
  • Develop and track model performance metrics across a variety of applications and data sets.
  • Integrate model development and deployment into cloud-based automated data processing pipeline.
  • Develop processes and algorithms for effective model retraining as necessary.
  • Data labeling: develop image labeling strategies for new model training and validation, including processes for on-going Q&A of deployed models. Evaluate labeling tools, including compatibility with AI training and validation systems.
  • Train and deploy models using Pytorch, MLFlow, Sagemaker in AWS.

Requirements

  • 3+ years of experience developing cloud-based AI solutions
  • Proficient in common deep learning tools, including PyTorch, PyTorch Lightning, and TensorFlow
  • Experience with multi-class models and hierarchical classification
  • Proficient in common programming languages, including Python, C++, Java

Bonus Points

  • MS degree in computer science, mathematics, engineering, or similar field
  • Proficient in Machine Learning Operations management, with extensive AWS experience, and demonstrated experience with complete model lifecycle management
  • Previous projects implementing Mask-RCNN and/or AWS Sagemaker
  • Experience with stereo and multi-view image data

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