Job Description:
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 on our electrical engineering teams. Our Engineering Team is responsible for giving life to the batteries, motors, and electronics that power solutions changing the lives of our users. Every developmental phase of these critical components happens in-house under the watch of this team. We continue to invest in electrical engineering resources to design and develop leadership in electronic capabilities; something unique within the industry. And we’re pushing the limits in firmware engineering, power electronics, embedded systems, machine learning, and the use of artificial intelligence.
Behind our doors you’ll be empowered every day to own it, drive it, and do what it takes to design and develop the biggest breakthroughs in the industry. Meanwhile, you’ll have the support and resources of the fastest-growing brand in the construction industry to make it happen.
Year after year, our team continues to make significant breakthroughs in the industry. We’re just getting started. To learn more about our story click HERE.
A Sr. ML Engineer on Cell Engineering will pioneer the integration of advanced data-driven and hybrid physics–ML methodologies into Lithium-ion cell engineering. This role will focus on applying machine learning techniques to develop predictive models, optimize cell design, incoming quality control, and product development processes. The ideal candidate will have a strong background in machine learning and data science, combined with a deep understanding of engineering principles, and will act as an independent driver for complex projects.
Duties and Responsibilities
- Develop and implement ML models to predict and optimize cell performance, degradation, and lifetime.
- Collaborate with electrochemists and design engineers to integrate ML insights into cell architecture and material selection.
- Integrate physics-based battery models with ML frameworks to improve performance prediction robustness and interpretability.
- Develop tools for early prediction of cycle-life, impedance growth, OCV drift, or self-discharge using engineering lab and ORT datasets.
- Use ML-driven simulations and optimization techniques to accelerate design cycles.
- Support Pack and Charger teams by developing ML models that translate cell-level data to pack performance, imbalance, or charge-acceptance behavior.
- Define acceptance criteria and drive organizational change for standardized data structures and integrity of the databases.
- Apply advanced analytics to correlate design parameters with performance outcomes.
- Collaborate with Quality team to create ML tools for spec optimization and MP drift detection.
- Build predictive models for incoming material quality and process variability.
- Deploy anomaly detection and root-cause analysis tools for supplier and production data.
- Act as a technical lead for ML initiatives across engineering teams.
- Mentor junior engineers and data scientists on ML best practices.
- Communicate via technical reports, presentations, and other documentation to communicate results and recommendations to internal and external stakeholders.
- Maintain knowledge of industry trends and emerging technologies related to Li-ion battery cell development.
Education and Experience Requirements
- Bachelor’s, or Master’s degree in Computer Science, Electrical Engineering, Mechanical Engineering, Data Science, or related fields with strong ML emphasis.
- Minimum 4+ years of hands-on experience in machine learning and data analytics.
- Proven track record of independently driving ML projects from concept to deployment.
- Experience with battery technology or electrochemical systems is highly desirable.
- Proficiency in Python, TensorFlow/PyTorch, and data visualization tools.
- Ability to integrate physics-based models with data-driven approaches
- Strong knowledge of supervised/unsupervised learning, deep learning, and statistical modeling.
- Familiarity with big data platforms and cloud computing (AWS, Azure, or GCP).
- Understanding of engineering principles related to energy storage systems.
- Knowledge of materials used in Lithium-ion cell industry for cathode, anode, separator etc., and materials characterization techniques is preferred
- Highly motivated self-driver with a never settle, always improving attitude.
- Excellent communication skills with a proven ability to collaborate effectively across cross-functional teams.
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.