Machine Learning Engineer II

Job title: Machine Learning Engineer II

About the Role As a Machine Learning Engineer II at Milwaukee Tool, you will create, develop, and validate machine learning models to power our battery-powered power tools. You will collaborate with cross-functional teams to deploy AI solutions into Milwaukee products worldwide, and contribute to the advancement of firmware, embedded systems, and edge AI.

What You'll Do

• Create, develop, and validate machine learning models and pipelines for embedded and edge devices.
• Collaborate with cross-functional teams to deploy ML solutions across Milwaukee Tool products globally.
• Explore and prototype new ML approaches for product improvements, and communicate technical concepts clearly; demonstrate ownership and proactive problem solving.
• Manage project tasks and ensure alignment with broader initiatives.

What We're Looking For

• Bachelor’s degree in Computer Science, Computer Engineering, Electrical Engineering or related discipline; completed coursework in ML/DS.
• At least one year of hands-on ML experience with embedded systems, edge computing, signal processing or related fields.
• Demonstrated experience applying ML algorithms in non-coursework settings (unsupervised/supervised learning, classification/regression, dimensionality reduction, model optimization).
• Experience with ML/AI methods such as CNNs, transformers, or computer vision.
• Proficient in Python; strong experience with libraries like NumPy, pandas, scikit-learn, Matplotlib.
• Experience with at least one deep learning framework (PyTorch or TensorFlow).
• Strong mathematical foundation in statistics, linear algebra, calculus, and optimization.
• Experience with modern software development tools and version control.
• Excellent technical communication and project management abilities; strong ownership of tasks.
• Ability to travel up to 10% (domestic and international).

Nice to Have

• Master’s degree or PhD in Machine Learning or related field preferred.
• At least three years of hands-on ML experience with embedded systems, edge computing, or signal processing.
• Experience with time series modelling and related domains such as NLP, SLAM, forecasting, or audio/video processing.
• Proven track record deploying AI/ML solutions aligned to business objectives.
• Proficient in C/C++ in embedded environments.
• Working knowledge of sensor technologies (IMU, thermistors, magnetic, optical) and interfacing to microcontrollers.
• Knowledge of embedded systems architecture (HW & SW), microcontroller design and operation.
• Experience with data collection methods and their value in relevant environments.
• Experience deploying ML algorithms to edge environments.
• Experience developing and deploying MLOps pipelines.

Compensation & Benefits

• Robust health, dental and vision insurance plans.
• Generous 401(k) savings plan.
• Education assistance.
• On-site wellness, fitness center, food, and coffee service.
• And many more, check out our benefits site.