Staff Software Engineer

At TE, you will unleash your potential working with people from diverse backgrounds and industries to create a safer, sustainable and more connected world. 

Job Overview

TE Connectivity’s R&D/Product Development Engineering Teams conceive original ideas for new products, introduce them into practice. They are responsible for product development, and qualification from market definition through production and release; assist in the qualification of suppliers for new products to ensure suppliers deliver quality parts, materials, and services for new or improved manufacturing processes; conduct feasibility studies, testing on new and modified designs; direct and support detailed design, testing, prototype fabrication and manufacturing ramp. The R&D/Product Development Engineering Teams provide all required product documentation including, but not limited to, Solid Model, 2D/3D production drawings, product specifications, and testing requirements. They create and modify detailed drawings and drafting or conceptual models from layouts, rough sketches or notes and contribute to design modifications to facilitate manufacturing operation or quality of product. Typical fields of expertise include: materials, mechanics and systems, electrical, optics, chemistry, software, automation systems, packaging, testing and measurement, and manufacturing of electrical, mechanical and electronic components, products, and their integration into systems.

Responsibilities

Strong proficiency in developing GUIs and UI automation using Python and Visual Basic.

Proven experience in building smart system-driven software solutions for automation in production environments, edge computing, and embedded systems.

Expertise in machine learning frameworks such as TensorFlow, PyTorch, or Scikit-learn.

Experience in developing ML models for predictive maintenance, anomaly detection, and real-time decision-making.

Solid understanding of communication protocols like I2C, SPI, UART, and USB, and their use in interfacing with embedded hardware.

Strong knowledge of electronic hardware and the ability to collaborate with hardware teams to develop smart system-powered integrated solutions.

Hands-on experience with real-time data processing and ML model integration for decision-making in production environments.

Proficiency with Git or other version control systems for software management.

Familiarity with task management tools like JIRA and Agile methodologies.

Ability to work independently, leading smart system integration efforts and collaborating across teams.

Experience in building and managing CI/CD pipelines for deploying smart system-driven solutions.

Strong problem-solving skills with a focus on smart system-enhanced solutions for process improvement.

 

 

Required Skill

Design and develop software-based GUIs/UI for automating manual processes in production line systems, embedded boards, and lab equipment.

Develop smart system-driven algorithms for predictive maintenance, process optimization, and decision-making using live data from edge devices.

Implement real-time data processing systems that leverage ML models to improve decision-making in automated production lines.

Integrate machine learning and deep learning techniques for predictive analysis, fault detection, and performance improvements in embedded systems and hardware.

Work with communication protocols such as I2C, SPI, UART, and USB to interface with electronic hardware for data collection and control.

Independently lead the development of ML models for tasks such as anomaly detection, predictive maintenance, and system optimization using data from sensors and production systems.

Utilize Python and Visual Basic to develop software solutions, with an emphasis on smart system integration for more intelligent automation and process optimization.

Build, train, and deploy machine learning models for real-time decision-making on edge devices and production lines.

Implement automated testing frameworks, including ML-driven test case generation and evaluation, to ensure robust software performance.

Work in an Agile environment, managing tasks using tools like JIRA, and utilize Git for version control.

Design and implement CI/CD pipelines for deploying smart system-powered applications and automating the software delivery process.

Competencies

Values: Integrity, Accountability, Inclusion, Innovation, Teamwork