Applied Machine Learning Engineer II - Advanced Engineering & Technology
AI summary of the role
This role is an individual contributor applied machine learning engineer on the Advanced Engineering & Technology team within the Power Tool Accessories business unit.
No longer in the current catalog. Last included 2026-09-09. Check the employer’s posting for availability.
What you’ll do
- Research and evaluate emerging AI/ML technologies, advancing them through the Technology Readiness Level (TRL) process from concept through integration.
- Frame engineering problems as ML problems, assessing ML value vs. physics-based or analytical approaches.
- Design, train, evaluate, and deploy ML models to solve applied science and engineering problems.
- Build end-to-end ML workflows spanning data acquisition, feature engineering, model development, validation, and deployment (PyTorch, TensorFlow, CUDA, Azure ML).
What you’ll bring
- BS in Mechanical Engineering, Electrical Engineering, Materials Science, Physics, Computer Science, Data Science, or related engineering discipline with advanced coursework or experience in Machine Learning.
- 3+ years applying ML to physical-world engineering or scientific problems (materials, mechanical systems, manufacturing, sensor systems, chemical processes, or similar).
- Strong working knowledge of Python and scientific computing ecosystem (NumPy, SciPy, Pandas, scikit-learn), with working knowledge of SQL.
- Hands-on experience with at least one deep learning framework (PyTorch or TensorFlow) and familiarity with cloud ML platforms (Azure ML, AWS SageMaker, or equivalent).
Technologies
PyTorch · TensorFlow · CUDA · Azure ML · AWS SageMaker · Python · NumPy · SciPy · Pandas · scikit-learn · SQL
About Milwaukee Tool
Designs and manufactures professional-grade cordless power tools and equipment for the construction, plumbing, and electrical trades, sold exclusively through The Home Depot in big-box US retail.
Acquired · 5000+ people
Source and classification
Internal deployment & tooling · Evidence for this classification:
Job Description: Applicants must be authorized to work in the U.S.; Sponsorship is not available for this position at this time. INNOVATE WITHOUT BOUNDARIES! At Milwaukee Tool we firmly believe that our People and our Culture are the secrets to our success - so we give you unlimited access to everything you need to create disruptive new technologies and solutions. Your Role on the Team: As a member of the Advanced Engineering and Technology (AET) Team in the Power Tool Accessories business unit you will utilize your expertise in machine learning to solve problems where no established solution exists and deliver first-of-its-kind technologies at Milwaukee Tool. You will research, prototype, and deliver ML-driven capabilities that accelerate how we design and develop products. You will take ideas from conceptual whiteboard architectures through functional prototypes and hand-off
More from the job description
Job Description: Applicants must be authorized to work in the U.S.; Sponsorship is not available for this position at this time. INNOVATE WITHOUT BOUNDARIES! At Milwaukee Tool we firmly believe that our People and our Culture are the secrets to our success - so we give you unlimited access to everything you need to create disruptive new technologies and solutions. Your Role on the Team: As a member of the Advanced Engineering and Technology (AET) Team in the Power Tool Accessories business unit you will utilize your expertise in machine learning to solve problems where no established solution exists and deliver first-of-its-kind technologies at Milwaukee Tool. You will research, prototype, and deliver ML-driven capabilities that accelerate how we design and develop products. You will take ideas from conceptual whiteboard architectures through functional prototypes and hand-off integrations, delivering technology innovation to product and production engineering teams. This role is an individual contributor position focused on applied execution and technology demonstration, working under shared technical direction. Why This Role is Different: Full‑Stack ML in a Physical Domain: Work across the ML stack, from machine and sensor‑level data through model deployment on edge hardware or cloud infrastructure. R&D Engineering First: Apply ML across Technology Readiness Levels (TR [... source excerpt omitted ...] ms on edge hardware and cloud infrastructure to support engineering decisions. Prepare technology transfer packages by documenting architecture decisions, known limitations, data requirements, and deployment specifications to enable technology adoption. Collaborate with cross-functional teams to deliver ML solutions aligned with engineering needs. Identify and assess emerging technologies via literature, universities, conferences, and vendor engagement. What You’ll Bring: Required BS in Mechanical Engineering, Electrical Engineering, Materials Science, Physics, Computer Science, Data Science, or related engineering discipline, with advanced coursework or experience in Machine L
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