Transportation Industry Machine Learning Specialist
3 days ago
About Our Team
At MLS Technologies, we are seeking a highly skilled Transportation Industry Machine Learning Specialist to join our team. As a Senior Embedded Controls and AI Engineer, you will design and develop scalable AI solutions using AI tools and machine learning models for the transportation industry.
Your Responsibilities
- Design and develop real-time AI solutions for transportation industry maintenance equipment.
- Implementing appropriate ML algorithms.
- Write clean, documented code following best practices.
- Develop and implement communication protocols.
- Work independently and collaboratively with a motivated team.
- Generate requirements and design documentation.
- Plan for, design, and deliver testing, and tested products into the QA process.
- Apply communication and problem-solving skills to solve software issues related to the design, development, deployment, testing, and operation of systems.
Requirements
- Master's / Bachelor's degree in Software Engineering or similar experience.
- 5+ years of experience in developing CNN, R-CNN type neural networks for computer vision tasks.
- 5+ years of experience in software development using C++ & Linux embedded.
- Experience with Supervised and Semi-Supervised Learning, Deep Learning, Support Vector Machines, Linear and Logistic Regression.
- Working knowledge of AI frameworks such as TensorFlow, Caf?, PyTorch, Keras, Darknet, and OpenCV.
- Working knowledge of AI edge devices such as NVIDIA Jetson / Nano / Orin.
- Knowledge of the Linux Operating System.
Preferred Experience
- Experience using statistical computer languages (R, Python, SQL etc.) to manipulate data and draw insights from large data sets.
- Experience working with and creating data architectures.
- Knowledge of a variety of machine learning techniques (semantic segmentation, clustering, decision tree learning, artificial neural networks, etc.) and their real-world advantages/drawbacks.
- Knowledge of advanced statistical techniques and concepts (regression, properties of distributions, statistical tests, and proper usage, etc.) and experience with applications.
- Experience with edge computing & controlling devices (On-device deployment in C/C++ or similar) for real-time application.
- Experience with optimizing neural networks to perform well on low-power mobile platforms (e.g. pruning, distillation, quantization).
Estimated Salary: $130,000 per year.
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