Computer Vision Engineer

Added: 5/5/2021

REF: 10033

Contract: Permanent

Location: California, United States

We are a rapidly expanding PropTech leveraging a proprietary data platform that informs every aspect of the decision making process in commercial/residential real-estate investing and insurance. We provide AI-Driven software solutions that ingest, organize, and analyze data for properties to unlock essential insight that guides  transactions by making every property thoroughly understood. 

The Role:
We are looking for a Senior Machine Learning Engineer to join our MLE team. You are someone that is passionate about leveraging technology to solve complex, real-world problems. You will train computer vision models on geospatial and satellite imagery and play a critical role in scaling our machine learning infrastructure. 

The Responsibilities:
  • Improve our semantic segmentation and image classification models
  • Train computer vision models to analyze geospatial and satellite image data 
  • Integrate new sources of pertinent data and information 
  • Understand the relationship between weathering conditions and natural sciences on property valuation & risk 
  • Increase efficiencies of labeling, curating, and training data 
  • Optimize the speed of predictions on our available GPUs
  • Expand and improve our ML code base
  • Lead initiatives to branch out and implement new ML systems, processes, and techniques
  • Evolve our tech stack and Computer Vision techniques by implementing cutting-edge research to our problems. 
  • Work cross-functionally with the data engineering and data science teams  

Technical Qualifications:
  • B.S. and 5+ years of experience or an Advanced Degree and 2+ years of experience in a quantitative discipline (i.e. computer science, physics, mathematics, statistics, earth sciences, etc.) 
  • Deep understanding of ML design principals 
  • Experience training deep learning models for computer vision
  • Demonstrated knowledge of ML fundamentals 
  • Excellent coding skills (i.e. data structures, algorithms, etc)
  • Strong Python skills and experience with modern deep learning frameworks (i.e. TensorFlow/Keras, PyTorch, etc.) 
  • Experience with data science tools like numpy, pandas, scikit-learn, Jupyter Notebooks, etc. 
  • Experience writing complex SQL data queries 
  • Experience with cloud hosted infrastructure (i.e. AWS, GCP, or Azure), relational database tools, and git/GitHub. 

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