DUST is a cutting-edge physical identity technology that provides an unbreakable bond between valuable assets and their digital records. Founded in 2018, DUST Identity is an MIT spinoff, backed by top-tier VCs, that is taking on a vast global market opportunity security supply chains and marketplaces. We aim high, and need self starters and problem solvers who thrive when challenges are great, and potential is greater.

We are looking for knowledge and experience, but above all care about character and cultural fit.

DUST Identity is an equal opportunity employer.

Responsibilities:

  • Develop machine vision algorithms and solutions
  • Develop performance testing and validation methodologies and reliable performance measures for algorithm evaluation
  • Drive the development of new tooling in support of the above
  • Design and implement machine learning models
  • Effectively communicate needs, challenges, and trade offs, with the rest of the engineering team

Requirements/Experience:

  • Deep knowledge of computer/machine vision fundamentals
  • BS/MS in Computer Science, Engineering, or similar fields
  • 5+ years successful track record of working on machine vision products
  • Experience writing technical reports, Standard Operating Procedures, and documentation
  • Experience with traditional machine learning, as well as deep learning, specifically models used for image classification, filtering, segmentation

Skills:

  • Feature extraction from images using established and cutting-edge deep learning approaches
  • Semantic Image Segmentation
  • Efficient and scalable image indexing and retrieval for large datasets
  • Python, OpenCV, numpy/scipy/etc., scikit-learn/image, jupyter
  • TensorFlow or PyTorch
  • Excellent mathematical reasoning skills; strong foundations in probability and statistics

Extra Credit:

  • Experience with hardware optimization and/or image sensor integration (e.g., DSPs, ASICs, FPGAs)
  • Unsupervised, learning-based feature extraction techniques
  • Sensor error modeling and propagation
  • Ph.D. in Computer Science, Electrical Engineering or a related field

Start Date: Immediately; Must be authorized to work in the United States
Location: Framingham, MA or Princeton, NJ
Compensation: Market Competitive + Stock option plan