1 day ago
Milwaukee, WI, USAMid Level
Responsibilities
- Design, develop, deploy, validate, and support machine learning solutions for manufacturing and service operations.
- Contribute to the full machine learning lifecycle, including data engineering, model development, deployment, monitoring, and scaling.
- Apply machine learning and AI methods to operational problems such as forecasting, predictive maintenance, defect detection, anomaly detection, and process optimization.
- Build and maintain data pipelines using Databricks and Spark against large operational datasets.
- Deploy machine learning solutions to Azure, Databricks, production environments, and edge devices.
- Partner with global operations, quality, supply chain, engineering, service, and plant teams to deliver measurable business value.
- Translate complex machine learning deployments for non-technical audiences and collaborate across international time zones.
- Travel domestically and internationally up to 20% of the time.
Requirements
- Bachelor of Science in computer science, computer engineering, electrical engineering, or another scientific or engineering discipline.
- At least one year of hands-on experience applying machine learning principles and algorithms to real-world problems.
- Coursework or specialization in machine learning or data science using deep learning frameworks such as PyTorch, TensorFlow, or Keras.
- Experience with supervised or unsupervised learning, classification, regression, dimensionality reduction, and model optimization outside coursework.
- Experience with CNNs, transformers, or computer vision.
- Proficiency with Spark, SQL, Python, NumPy, pandas, scikit-learn, and Matplotlib.
- A strong mathematical foundation in statistics, linear algebra, calculus, and optimization.
- Experience with machine learning deployments using CI/CD pipelines, Azure, Databricks, and MLFlow, plus edge devices, GPUs, containerization, and Linux.
- Strong problem-solving and technical communication skills, with experience collaborating across global teams.
- A master's degree or PhD in machine learning or a related field is preferred.
- Three or more years of hands-on machine learning experience, time-series modeling, computer vision, measurable operations outcomes, desktop or web application development, data engineering, MLOps, edge deployment, or generative AI experience are preferred.
Benefits
- Health, dental, and vision insurance.
- 401(k) savings plan.
- Education assistance.
- On-site wellness facilities, fitness center, food, and coffee service.
- The role supports domestic and international travel up to 20% and may require schedule adjustments for international time zones.
Tech Stack
Categories
Data EngineeringML Engineering
About TTI, Inc.
TTI, Inc. is a specialty distributor of passive, interconnect, electromechanical, and discrete semiconductor components for industrial, aerospace, defense, and consumer electronics manufacturers. Founded in 1971 and headquartered in Fort Worth, Texas, it offers supply chain services and value-added capabilities such as connector assembly, and operates globally as a Berkshire Hathaway company.