The Applied Machine Learning Engineer II will utilize their machine learning expertise to deliver innovative technologies and accelerate product development in the Power Tool Accessories business ...
The Applied Machine Learning Engineer II will utilize their machine learning expertise to deliver innovative technologies and accelerate product development in the Power Tool Accessories business ...
Milwaukee Tool is a company that values innovation and culture, and they are seeking an Applied Machine Learning Engineer II to join their Advanced Engineering and Technology team. This role involves ...
Milwaukee Tool is a company that values innovation and culture, and they are seeking an Applied Machine Learning Engineer II to join their Advanced Engineering and Technology team. This role involves ...
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Senior MLOps Engineer (Remote)
Menomonee Falls, WI · On-site
$104K - $144K/yr
Contribute to the roadmap for Machine Learning Engineering and Data Science tools, including ... developing reusable frameworks and standardized solutions to streamline model implementation
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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 ...
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 ...
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 ...
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 ...
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 ...
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 ...
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 ...
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 ...
... Machine Learning Engineer (Associate - MLA-C01) or AWS Certified Data Engineer (Associate) * 1+ years of experience building reliable, maintainable, and well-documented code * Ability to travel 50 ...
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Machine Learning Engineer Associate information
See Milwaukee, WI salary details
$40.9K - $49K
1% of jobs
$49K - $57.1K
6% of jobs
$57.1K - $65.2K
17% of jobs
$65.3K is the 25th percentile. Wages below this are outliers.
$65.2K - $73.3K
22% of jobs
The median wage is $75K / yr.
$73.3K - $81.4K
18% of jobs
$81.4K - $89.5K
10% of jobs
$90.2K is the 75th percentile. Wages above this are outliers.
$89.5K - $97.6K
10% of jobs
$97.6K - $105.7K
8% of jobs
$105.7K - $113.8K
4% of jobs
$113.8K - $121.9K
2% of jobs
$121.9K - $130.1K
2% of jobs
$40.9K
$81.4K
$130.1K
How much do machine learning engineer associate jobs pay per year?
What are some common challenges faced by machine learning engineer associates when deploying models to production?
What is a machine learning engineer associate?
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Applied Machine Learning Engineer II - Advanced Engineering & Technology
Brookfield, WI • On-site
Full-time
Re-posted 4 days ago
Job description
Milwaukee Tool is a company that values innovation and culture, seeking to create disruptive technologies and solutions. The Applied Machine Learning Engineer II will utilize their machine learning expertise to deliver innovative technologies and accelerate product development in the Power Tool Accessories business unit.
Responsibilities:
• Research and evaluate emerging AI and ML technologies, advancing them through the Technology Readiness Level (TRL) process from concept through technology integration.
• Frame engineering problems as ML problems by assessing ML value versus physics‑based or analytical approaches and defining practical success criteria.
• Design, train, evaluate, and deploy ML models to solve applied science and engineering problems that expand product development capabilities.
• Build end‑to‑end ML workflows spanning data acquisition, feature engineering, model development, validation, and deployment (PyTorch, TensorFlow, CUDA, Azure ML).
• Deploy ML enabled systems 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.
Qualifications:
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 Learning.
• +3 or more years of experience applying ML to physical-world engineering or scientific problems (materials, mechanical systems, manufacturing, sensor systems, chemical processes, or similar).
• Demonstrated experience designing, training, evaluating, and deploying ML models on real-world problems.
• Strong working knowledge of Python and the 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).
• Strong mathematical foundations in linear algebra, probability, statistics, and optimization, with the ability to reason about loss functions, convergence behavior, and model assumptions.
• Demonstrated ability to formulate ambiguous engineering or scientific problems into well-defined ML problems with clear objectives and evaluation criteria.
• Curiosity‑driven approach to learning new technologies and methods, with emphasis on applying machine learning to real‑world scientific and engineering challenges.
• Ability to work across a diverse range of data types.
• Hands-on approach to collaboration and evaluation of technologies.
• Ability to thrive in an ambiguous and fast-paced environment, where problem definitions evolve.
• Ability to travel 10% of the time (domestic and international).
Preferred:
• Master’s Degree or PhD in relevant field.
• Familiarity with physics-informed ML approaches, embedding physical constraints in model architecture, or surrogate modeling for simulation acceleration.
• Experience with computer vision for engineering applications.
• Exposure to edge deployment: model optimization containerized deployment to industrial hardware.
• Experience with design of experiments (DOE), uncertainty quantification, or Bayesian optimization.
• Familiarity with version control, experiment tracking, and reproducible research practices.
Company:
Milwaukee Tool manufactures electric power tools and accessories. It is a sub-organization of Techtronic Industries. Founded in 1924, the company is headquartered in Brookfield, USA, with a team of 5001-10000 employees. The company is currently .