Staff Machine Learning Engineer

Job Overview

The pace of innovation in artificial intelligence and machine learning continues to accelerate, and the Data and Devices Business Unit is at the center of this transformation. Our customers are building intelligent systems that redefine how data is processed, analyzed, and used across compute, networking, and cloud infrastructure. At TE Connectivity, we support this evolution by delivering scalable, high-quality software solutions that enable next-generation products.

This role is a strong fit for someone with a solid software and analytical foundation who is eager to apply machine learning techniques to real engineering problems. You will work closely with experienced engineers, data scientists, and cross functional teams to develop models, improve workflows, and support the integration of ML capabilities into our tools and processes.

What you will be doing…
As a Machine Learning Engineer, you will support the development, testing, and deployment of ML models and data driven software solutions. You will contribute to data preparation, model development, performance analysis, and software implementation while building a strong understanding of engineering applications in a production environment. 

Key Responsibilities

Machine Learning Development

• Support the design, development, and testing of machine learning models for engineering and business applications.
• Assist with data preparation, feature engineering, model training, and validation.
• Evaluate model performance and help identify opportunities for improvement.
• Contribute to the implementation of ML pipelines and workflows for repeatable model development.

Software Engineering and Tools

• Develop clean, maintainable, and well documented code in support of ML applications and data workflows.
• Assist with integrating ML models into internal tools, platforms, or engineering systems.
• Support debugging, testing, and optimization of software and model performance.
• Participate in code reviews and follow software development best practices.

Data Analysis and Problem Solving

• Analyze structured and unstructured data to identify patterns, trends, and improvement opportunities.
• Work with cross functional teams to understand business and engineering problems and translate them into data driven solutions.
• Prepare summaries, dashboards, or technical reports to communicate findings and recommendations.

Collaboration and Learning

• Collaborate with software engineers, product teams, and domain experts on project execution.
• Learn from senior team members and apply feedback to improve technical and professional skills.
• Stay current with foundational machine learning methods, tools, and industry trends.

What your background should look like

• Bachelor’s with 8+ years, Master’s with 6+ years, or PhD with 3+ years of experience in Computer Science, Data Science, Software Engineering, Electrical Engineering, or a related technical discipline.
• Strong programming skills in Python
• Experience with machine learning frameworks such as PyTorch, TensorFlow, or scikit learn
• Experience working with data analysis libraries such as pandas or NumPy
• Familiarity with data pipelines, model evaluation, and machine learning experimentation
• Knowledge of software development practices, including version control and testing
• Strong analytical thinking and problem-solving skills
• Ability to collaborate effectively in cross-functional engineering teams
• Clear communicator who works well in a collaborative team environment.
• Self-motivated and eager to learn new technologies with guidance.
• Ability to travel occasionally, up to 10 percent, for team meetings or training as needed.

Competencies