Machine Learning Engineer

Overview

On Site
$1 - $2
Full Time
100% Travel

Skills

Machine Learning
Jax
TensorFlow
PyTorch
TensorFlow Lite
Lite RT
Core ML
MediaPipe
Android
iOS
AWS
Google Cloud
Azure

Job Details

We are seeking a passionate and technically skilled Machine Learning Support Engineer to join our team and focus on providing exceptional support to our developer community using our On-Device Machine Learning (ODML) technologies. This role will be centered around actively engaging with developers on open forums like GitHub, Stack Overflow, and our company's community platforms. You will be responsible for troubleshooting issues, providing guidance on best practices, and contributing to the improvement of our ODML tools and documentation. Your primary goal will be to ensure developers have a positive experience and are successful in building their applications with our ODML platform. Hands-on Coding in C++/Python experience at production level is preferred.

Experience:

Experience with one or more general purpose programming languages including but not limited to: C/C++, Python, Java/Kotlin, or Swift.

Experience with machine learning concepts and frameworks (e.g., Jax, TensorFlow, PyTorch etc).

Experience with on-device ML frameworks like TensorFlow Lite, Lite RT, Core ML, MediaPipe, or similar is highly desirable.

Experience with mobile application development (Android/iOS) or embedded systems programming and/or converting models to deploy in edge devices is a plus.

Experience working with open-source projects and developer communities is a significant advantage.

Understanding of software development workflows and tools (e.g., Git, issue tracking systems).

Familiarity with cloud computing platforms (e.g., AWS, Google Cloud, Azure) is a plus.

Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.