DUST Identity is looking for a Machine Vision Engineer to join our collaborative and multifaceted team of engineers dedicated to addressing vulnerabilities in the global supply chain.

HOW YOU WILL MAKE AN IMPACT

We are looking for a Machine Vision Engineer to join our growing R&D team. We are looking for knowledge and experience; but we care about character and cultural fit most of all. The Machine Vision Engineer will drive improvements in DUST's core technologies across a wide range of use cases and deployment scenarios.

The Machine Vision Engineer role requires a hands-on, results-oriented individual who is organized, a great communicator, and able to work in a fast-paced environment. The successful candidate will possess a technical background that enables them to identify, test, and deploy cutting-edge algorithms and data-processing techniques. Additionally, the candidate should have strong communication skills in order to explain their chosen technical approach and tradeoffs encountered when tackling problems. They should also have a demonstrated ability to execute within continuous development cycles.

ABOUT US

DUST Identity is a physical object security solution that uses nano-diamonds to securely tag physical objects so they are uniquely identifiable. Enabled by the development of new materials, cutting edge hardware, and exciting machine vision, DUST’s customers can ensure that every physical object - whether an airplane part, microprocessor, or priceless artifact - is genuine.

DUST aims to become the industry standard for physical object identification and security.

WHAT YOU WILL DO

  • 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

WHAT YOU BRING

  • Deep knowledge of computer/machine vision fundamentals
  • 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
  • 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

DETAILS

Start Date: Immediately. Must have legal right to work in the United States without sponsorship.

Location: Framingham, MA

Compensation: Market Competitive + Equity

DUST Identity is an equal opportunity employer.

PERKS

  • Award winning startup with a product that matters
  • Equity 401k
  • An abundance of snacks/coffee
  • Medical, dental, vision, LTD, and life insurance Flexible paid time off policy
  • Casual dress
  • Reverse commute with plenty of parking

Concerning Covid 19

At DUST Identity, we place the utmost importance on the health and safety of our team and our community. To do our part in limiting the spread, all team members that are able to work remotely during this time are doing so. We are sensitive to the individual concerns of each team member, and continue to reassess as more information and guidelines are released by the community.

While we hope that the DUST team will eventually return to in-person work, we will remain remote for the foreseeable future.