Senior Machine Learning Engineer

This is a unique opportunity to join a leading company in automotive innovation, where you can have a direct impact on future mobility solutions. As an ML Engineer, you will play a key role in enhancing automated driving experiences by working with advanced AI and machine learning algorithms.

You'll tackle complex challenges like optimising neural networks for embedded systems and improving multi-core device scheduling. In this role, you will collaborate with international experts in a dynamic, agile environment, contributing to projects that shape the future of mobility and automotive safety.

Key Responsibilities:

Machine Learning Deployment: Develop and optimise machine learning applications on both PC and embedded platforms using C/C++.
Neural Network Optimisation: Port and fine-tune neural networks for embedded platforms, leveraging techniques like quantization and pruning to maximise run time performance.
Efficient Software Design: Write high-quality, well-tested, and efficient C++ code for AI/ML software stacks while ensuring seamless system integration across various hardware components.
Core: Enhance the scheduling of multiple neural network models across different device cores to improve overall system performance.
Agile Collaboration: Work closely with a diverse team of machine learning engineers, system engineers, and software developers using Agile methodologies such as SCRUM.

Qualifications:

A Master's degree in Computer Science, Embedded Systems, or a related field.
Strong software development skills in C++, with a particular focus on writing clean, well-tested, and well-documented code.
Experience in integrating multiple software modules into one system and optimising system performance through process scheduling, threading, and resource allocation.
Familiarity with computing hardware architectures such as CPU, GPU, DSP, NPU, and AI accelerators.
Proficiency in Linux environments and working knowledge of version control systems like Git, build systems (Make, CMake), and code review tools (Gerrit, GitLab, Bitbucket).

Plus:

Flexibility: Enjoy a dynamic work environment that supports flexible working arrangements, including up to two days of home office per week.
Growth Opportunities: Benefit from continuous learning through internal and external training, coaching, and certifications that will help you develop professionally.
Recognition: Join a culture that celebrates innovation and rewards excellence, offering ample opportunities to showcase your technical skills and creativity.
Community Impact: Contribute to initiatives aimed at building safer, smarter, and more efficient transportation solutions.

Equal Opportunity Statement:

Committed to fostering an inclusive and diverse work environment. All qualified applicants will receive consideration for employment without regard to race, colour, religion, gender, sexual orientation, gender identity, national origin, disability, veteran status, or any other characteristic protected by applicable law. Creating a workplace where everyone can thrive, contribute, and grow.