Machine Learning Engineer II - Operations Milwaukee, WI

TTI Group; Milwaukee (WI); Hybrid; USD 120,000 - 160,000; Full time

Benefits offered by this job

Health insurance

401(k) savings

Education assistance

On-site wellness center

Coffee service

Job summary

Milwaukee Tool is seeking a Machine Learning Engineer II to design, develop, and deploy ML solutions that optimize manufacturing and service operations. You will work with operations, quality, supply chain, and engineering teams to implement data-driven solutions across global sites.

The role emphasizes end-to-end ML lifecycle, including data engineering, model development, and production monitoring on Azure and Databricks, with translation of complex ML work for non-technical audiences.

Qualifications

• Bachelor's degree in CS/CE/EE or related field.
• Coursework in ML/Data Science using DL frameworks (PyTorch, TensorFlow, Keras).
• Minimum one year applying ML to real-world problems.
• Experience with ML algorithms in practical settings (classification/regression).
• Experience with CNNs, transformers or computer vision.
• Proficiency in Spark, SQL and Python (NumPy, pandas, scikit-learn, Matplotlib).
• Strong math foundation in statistics, linear algebra, calculus and optimization.
• Experience with ML deployments using CI/CD (Azure, Databricks, MLFlow) and edge devices.
• Excellent problem-solving and technical communication skills.
• Experience working with global teams and travel up to 20%.

Responsibilities

• Design, develop, and deploy ML solutions to improve manufacturing and services.
• Collaborate cross-functionally with operations, quality, supply chain, engineering, and service teams.
• Contribute to the full ML lifecycle from data engineering to deployment and monitoring on Azure and Databricks.
• Partner with Global and Service Teams to deploy, validate, and support ML solutions in production environments.
• Deliver production-ready ML solutions with measurable operational value.

Skills

Python

Spark

SQL

Pytorch

TensorFlow

ML Deployment

CI/CD

Edge deployment

Communication

Team collaboration

Time zone coordination

Education

Bachelor of Science in CS/CE/EE

ML/Data Science coursework

One year ML experience

Tools

Databricks

Azure

MLFlow

GPU

Linux

Job description

Machine Learning Engineer II - Operations

We value our talented employees, and whenever possible strive to help one of our associates grow professionally before recruiting new talent to our open positions.

Our people make all the difference in our success.

Applicants must be authorized to work in the U.S.; Sponsorship is not available for this position at this time.

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 drive disruptive new technologies and solutions across our operations teams. Our Operations Teams are responsible for the manufacturing, service, supply chain, and quality systems that bring our products to life and into the hands of our users. We continue to invest in advanced analytics, machine learning, and AI capabilities to transform how we run our plants, optimize production, and anticipate issues before they reach the line. We’re pushing the limits in data engineering, deep learning, and generative AI applied to real-world manufacturing problems.

Your role on our team:

As a Machine Learning Engineer II, you will design, develop, and deploy machine learning solutions that improve how Milwaukee Tool manufactures and services products. Working cross-functionally with operations, quality, supply chain, engineering, and service teams, you will develop and implement data-driven solutions that address real-world business and operational challenges globally.

You will contribute to the full machine learning lifecycle, from data engineering and model development to deployment and monitoring on Azure and Databricks. A key aspect of this role is partnering with our Global and Service Teams to deploy, validate, and support machine learning solutions in operational environments, ensuring models deliver measurable value where they are used.

This role is ideal for a self-motivated engineer who thrives in a fast-paced environment, communicates effectively across technical and non-technical teams, and takes ownership of delivering impactful, production-ready solutions.

What TOOLS you’ll bring with you:

• Bachelor of Science Degree in Computer Science, Computer Engineering, Electrical Engineering or other scientific or engineering discipline.
• Completed course work or specialization in Machine Learning and/or Data Science using one or more deep learning frameworks (PyTorch, TensorFlow, Keras, etc).
• At least one year of hands-on experience applying machine learning principles and algorithms to dynamic, real-world problems.
• Demonstrated experience applying fundamental machine learning algorithms and techniques in a non-coursework setting (e.g. unsupervised or supervised learning, classification/regression, dimensionality reduction, model optimization).
• Demonstrated experience with machine learning and AI methods such as CNNs, transformers, or computer vision.
• Proficiency in big data transformation using Spark, SQL, and Python (NumPy, pandas, scikit-learn, Matplotlib).
• Sold mathematical foundation in statistics, linear algebra, calculus and optimization.
• Experience working with ML deployments using CI/CD pipelines (Azure, Databricks, MLFlow) and edge devices (GPU, Containerization, Linux).
• Excellent problem-solving and technical communication skills translating complex ML deployments into language that non-technical audience can understand.
• Experience collaborating with global teams, including a willingness to adjust working hours to accommodate international time zones and ensure project alignment.
• Ability to travel up to 20% of the time (domestic and international).

Other TOOLS we prefer you to have:

• Master’s degree or PhD in Machine Learning or related field is preferred.
• At least three years of hands-on experience applying machine learning principles and algorithms to dynamic, real-world problems.
• Experience with time-series modeling for use cases such as demand forecasting, predictive maintenance, yield prediction, or process anomaly detection.
• Experience with computer vision for use cases such as defect detection, missing part detection, part quality inspection, part counting, etc.
• Proven track record of developing, deploying, and scaling AI or ML solutions tied to measurable operations outcomes (e.g. scrap reduction, throughput, OEE, on-time delivery, inventory turns).
• Desktop application or Web app development experience (e.g. building tools or UIs that put models in the hands of plant and operations users).
• Hands-on data engineering experience building pipelines on Databricks/Spark against large operational datasets (MES, ERP, SCADA, IoT/Sensor Telemetry).
• Experience applying generative AI or LLMs to operations problems such as knowledge retrieval, document processing, or assistive tooling for plant teams.
• Experience in developing, maintaining and using MLOps pipelines and ensure efficient deployment, monitoring, and scaling of ML models in production.
• Experience developing and deploying machine learning algorithms to edge environments.

We provide these great perks and 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 HERE.

Milwaukee Tool is an equal opportunity employer.