COMPANY OVERVIEW

At Motorola Solutions, we believe that everything starts with our people. We’re a global close-knit community, united by the relentless pursuit to help keep people safer everywhere. Our critical communications, video security and command center technologies support public safety agencies and enterprises alike, enabling the coordination that’s critical for safer communities, safer schools, safer hospitals and safer businesses. Connect with a career that matters, and help us build a safer future.

BASIC REQUIREMENTS

• Master’s degree in a technical field.
• 5+ years of professional experience in machine learning engineering, with a focus on deploying models to edge devices.
• Strong understanding of model optimization techniques (quantization, pruning, knowledge distillation).
• Experience in C++/Python programming and working with embedded systems.
• Strong communication skills and ability to work collaboratively in a team-oriented environment.

TRAVEL REQUIREMENTS

Under 10%

THIS ROLE IS PRIMARILY HYBRID WITH WEEKLY TRAVEL INTO OUR LONDON OFFICES AROUND 2 DAYS A WEEK.

As a Senior Machine Learning Engineer, you will focus on deploying AI/ML models to a variety of edge devices, with particular expertise in converting models for Ambarella and Novatek SoCs. You will collaborate with cross-functional teams to ensure the efficient integration and optimization of models, ensuring they run seamlessly on low-power, resource-constrained devices.

KEY RESPONSIBILITIES

• Convert, optimize, and deploy deep learning models for edge devices, focusing on Ambarella and Novatek SoCs.
• Collaborate with data scientists, hardware engineers, and software developers to tailor models for resource-constrained environments.
• Develop and implement model compression, quantization, and pruning techniques to improve performance.
• Work closely with edge device firmware teams to ensure seamless integration of models and efficient execution on device hardware.
• Contribute to the continuous improvement of machine learning deployment processes and tools within the organization.