Navigation & Machine Learning Engineer Intern

Apply your knowledge of machine learning technologies to cutting edge products and tackle complex engineering challenges. Joining Trimble Applanix, you will gain hands-on experience developing advanced firmware for real-time navigation systems while collaborating with a high-performing engineering team.

What Makes This Role Great

In this role, you will be at the forefront of implementing cutting edge machine learning algorithms directly into navigation firmware, directly influencing system performance and shaping the future of autonomous positioning technology.

Key Exciting Responsibilities

• Take part in machine learning development activities related to Trimble Applanix APX/AP+ firmware.
• Drive critical engineering activities including debugging, data analysis, and algorithm implementation for real-time systems.
• Develop software using industry standard development tools such as GIT and JIRA within an agile team framework.
• Collect, structure, and organize high quality datasets to power continuous navigation model improvements.
• Produce comprehensive technical documentation to support system level integration and ongoing development.

Essential Skills & Experience

• Enrolled in a Masters or PhD program in Electrical Engineering, Computer Engineering, Aerospace Engineering, or Mechatronics Engineering.
• Demonstrated experience with Google Tensor Python development.
• Practical experience with TinyML library deployment in MCU environments.
• Strong technical expertise in Kalman filtering and machine learning techniques.
• Fluent software development skills using C/C++ languages in real-time and Linux environments.

Bonus Points For

• Knowledge of system level integration and multi-component hardware/software development.
• Proven ability to multi-task effectively in a dynamic, highly agile environment.
• Strong presentation skills and ability to communicate technical findings clearly.

Logistics

Location: Richmond Hill, Ontario (In-Office)

Travel Requirement: 0%

Start Date: May 2027

Why You'll Love Working With Us

At Trimble, we're not just a company that "does good"—we are a team dedicated to making a tangible, positive Real-World Impact.

We build innovative solutions designed to solve the world's most critical challenges. From construction sites to transportation hubs, our work tangibly improves how people live, build, move, and grow.

• You'll work on projects that truly matter: Our purpose-driven culture means you'll be helping to build and deliver solutions that make work faster, safer, and more sustainable for millions of people worldwide. Our impact is tangible, from connected machines that save fuel to data-driven insights that reduce waste.
• Collaborate with like-minded people: Our strong internal culture is a "hidden gem." You will work with a collaborative, supportive team that shares your purpose and fosters a genuine sense of belonging. We're a company of "visionary pragmatists" who think boldly and build things that work.
• Be an owner: Trimble thrives on individuals who take initiative and embrace ownership. You'll find an entrepreneurial spirit where success is often "self-authored," empowering proactive "doers."

Navigation Engineering, Machine Learning Intern, TinyML, Kalman Filtering, C++, Python, Linux, Firmware Development, MCU, Applanix

How to Apply

Please submit an online application for this position by clicking on one of the Apply buttons located in this posting.

Join a Values-Driven Team: Belong, Grow, Innovate.

At Trimble, our core values of Belong, Grow, and Innovate aren't just words—they're the foundation of our culture. We foster an environment where you are seen, heard, and valued (Belong); where you have an opportunity to build a career and drive our collective growth (Grow); and where your innovative ideas shape the future (Innovate). We believe in empowering local teams to create impactful strategies, ensuring our global vision resonates with every individual. Become part of a team where your contributions truly matter.

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