About the Role
We’re looking for a Senior Machine Learning Engineer to join our Advanced Development group in Cambridge. You’ll work on Edge AI — deploying, optimising, and scaling intelligent models directly on-device. These are models that run locally on constrained environments, enabling faster, smarter, and more private user experiences.
This is a hands-on, high-impact role for someone who thrives in an environment where innovation meets engineering excellence. You’ll collaborate with a world-class team of software and hardware engineers, contributing across the entire lifecycle of building, optimising, and delivering next-generation intelligent systems.
What You’ll Be Doing
Designing, developing, and deploying machine learning models on embedded and edge platforms, balancing latency, performance, and efficiency.
Implementing and optimising AI inference pipelines for hybrid (device + cloud) deployments.
Writing high-performance C and modern C++ code for Linux-based embedded systems.
Partnering with cross-functional teams to define architecture, integration, and performance targets for new AI-driven features.
Driving innovation by exploring emerging AI frameworks, quantisation techniques, and neural network optimisation methods suitable for constrained hardware.
Contributing across design, implementation, testing, release, and maintenance, taking full ownership of your work from prototype to production.
We’re Excited If You Have
Strong proficiency in C and modern C++, with the ability to write efficient, maintainable, and optimised code.
Experience developing, debugging, or deploying software on Linux-based embedded platforms.
Proven success in building or integrating machine learning models for on-device inference.
Familiarity with frameworks such as TensorFlow Lite, ONNX Runtime, or PyTorch Mobile.
A solid understanding of embedded system architecture, performance trade-offs, and resource constraints.
A collaborative mindset, with the ability to work across software, hardware, and research disciplines.
A degree in Computer Science, Electrical Engineering, Machine Learning, or a related field — or equivalent practical expertise.
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Benefits
Roku is committed to offering a diverse range of benefits as part of our compensation package to support our employees and their families. Our comprehensive benefits include global access to mental health and financial wellness support and resources. Local benefits include statutory and voluntary benefits which may include healthcare (medical, dental, and vision), life, accident, disability, commuter, and retirement options (401(k)/pension). Our employees can take time off work for vacation and other personal reasons to balance their evolving work and life needs. It's important to note that not every benefit is available in all locations or for every role. For details specific to your location, please consult with your recruiter.
The Roku Culture
Roku is a great place for people who want to work in a fast-paced environment where everyone is focused on the company's success rather than their own. We try to surround ourselves with people who are great at their jobs, who are easy to work with, and who keep their egos in check. We appreciate a sense of humor. We believe a fewer number of very talented folks can do more for less cost than a larger number of less talented teams. We're independent thinkers with big ideas who act boldly, move fast and accomplish extraordinary things through collaboration and trust. In short, at Roku you'll be part of a company that's changing how the world watches TV.
We have a unique culture that we are proud of. We think of ourselves primarily as problem-solvers, which itself is a two-part idea. We come up with the solution, but the solution isn't real until it is built and delivered to the customer. That penchant for action gives us a pragmatic approach to innovation, one that has served us well since 2002.
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