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.

We are looking for a motivated early-career software engineer with a strong interest in AI and ML. This role offers hands-on exposure to real-world engineering problems, collaboration with experienced engineers, and the opportunity to grow technical depth in a fast-moving, data-driven environment.

What you will be doing…

As an AI ML Software Engineer, you will work as part of a cross-functional team supporting the development of software tools, models, and infrastructure used in compute, AI, and data communication systems. You will contribute to building, testing, and improving AI ML solutions while learning how these technologies are applied in production environments. This role provides mentorship from senior engineers and opportunities to expand your skills across the full software development lifecycle.

Responsibilities:

1. Software Development and Engineering Support

• Contribute to the development and maintenance of software components used in AI ML workflows.
• Assist in implementing machine learning models, data pipelines, and supporting tools under guidance from senior engineers.
• Write clean, maintainable, and well-documented code following established best practices.
• Support debugging, testing, and performance analysis of software and models.
• Participate in code reviews and incorporate feedback to improve software quality.

2. AI ML Model Development and Data Analysis

• Assist in data preparation, feature engineering, and model training activities.
• Support evaluation of model performance using standard metrics and validation techniques.
• Help analyze experimental results and summarize findings for the broader team.
• Learn and apply common ML techniques such as supervised learning, basic deep learning, or statistical modeling.

3. Collaboration and Cross Functional Work

• Work closely with software engineers, data scientists, and system architects to understand requirements and use cases.
• Support integration of AI ML components into larger systems and workflows.
• Communicate progress, challenges, and results clearly in team meetings and written updates.
• Contribute to internal documentation and knowledge sharing efforts.

4. Learning and Technical Growth

• Stay current with foundational AI ML concepts, tools, and frameworks.
• Participate in technical training, design reviews, and team discussions.
• Take ownership of small projects or tasks to build confidence and technical depth over time.

Desired Candidate Profile:

• Bachelor’s degree in Computer Science, Software Engineering, Electrical Engineering, or a related field.
• 5+ years of relevant experience in software development, AI, ML, or data-focused roles.
• Understanding of machine learning fundamentals and algorithms.
• Experience programming in Python and familiarity with at least one ML framework such as PyTorch, TensorFlow, or scikit learn.
• Familiarity with data structures, algorithms, and basic software engineering principles.
• Exposure to version control systems such as Git.
• Strong problem-solving and analytical skills with attention to detail.
• Clear communicator who works well in a collaborative team environment.
• Self-motivated and eager to learn new technologies with guidance.
• Effective communicator, capable of presenting technical findings and collaborating across teams.

• Ability to spend 10%-25% of your time traveling to customers, conferences, and TE development sites.

What your background should look like

Generally requires Bachelors degree in appropriate field with a minimum of 5 years of progressively responsible professional level experience; Masters degree or higher or local equivalent may be preferred at this level

Competencies