Embedded AI Scientist for Tiny-Device ML (Hybrid)

Wasatch Photonics

Morrisville (NC)

Hybrid

USD 90,000 - 120,000

Full time

14 days+

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Benefits offered by this job

Work with leading scientists
Flexible schedule
Profit-sharing

Job summary

Wasatch Photonics in Morrisville, North Carolina, seeks an Embedded Data Scientist to develop AI models for embedded microcontrollers in handheld spectroscopic instruments. Ideal candidates will have experience with TensorFlow, Keras, and Python, alongside a degree in a relevant field.

This position combines machine learning with embedded systems in a collaborative environment with opportunities for limited hybrid work. Join us to make an impact in sectors like healthcare and environmental monitoring.

Qualifications

  • 2+ years experience with TensorFlow and Keras.
  • 2+ years experience in Python development.
  • 1+ years experience in embedded languages like C or Rust.
  • 1+ years experience in version control systems such as Git.
  • Willingness to learn about optical systems.

Responsibilities

  • Maintain Python process for training data generation.
  • Analyze model quality against ground truth.
  • Optimize models for embedded microcontroller execution.
  • Support data collection for ML model development.

Skills

Machine-learning frameworks (TensorFlow, Keras)
Python
Embedded languages (C, Rust)
Git
Communication skills

Education

Bachelor’s degree in Mathematics, Data Science, Computer Science, Computer Engineering or related discipline

Tools

LiteRT
STM32N6

Job description

Wasatch Photonics in Morrisville, North Carolina, seeks an Embedded Data Scientist to develop AI models for embedded microcontrollers in handheld spectroscopic instruments. Ideal candidates will have experience with TensorFlow, Keras, and Python, alongside a degree in a relevant field.

This position combines machine learning with embedded systems in a collaborative environment with opportunities for limited hybrid work. Join us to make an impact in sectors like healthcare and environmental monitoring.

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