Machine Learning Engineer

About the position

The Machine Learning (ML) Engineer's primary role is to implement and optimize machine learning algorithms for BrainChip's Akida Neuromorphic System-on-Chip (NSoC). This role requires a strong practical proficiency in ML, particularly in embedded AI. The ML Engineer will work on applications such as computer vision, audio processing, Language Models, Radar Processing, etc. The candidate is expected to have excellent command of at least one programming language, broad and comprehensive understanding of machine learning, and a solid mathematical foundation.

Responsibilities

• Develop industry learning edge algorithms for state of the art, novel computer architectures
• Assist the team in pioneering new algorithms in Generative Edge AI
• Working closely with the research team to translate ML models from theory to practice
• Developing and maintaining efficient code in Python, C, and C++ for use in a fast pace research environment
• Staying current with advancements in ML, embedded AI, and related technologies
• Collaborating on ML algorithm/hardware co-design tasks to enhance system performance
• Debugging and Benchmarking software to ensure optimal performance on the Akida hardware
• Interfacing with customers to understand their needs and provide technical support for ML applications
• Contributing to the development of the Akida software stack and toolchain
• Contributing to Patent and Publications.

Requirements

• Must be a US citizen for this role
• Bachelor's Degree in Computer Engineer, Computer Science, Electrical Engineering, or a related field with 5+ years of experience; or a Master's Degree with 3+ years of experience
• Strong background in machine learning and embedded AI through a well regarded university program or through extensive self-study
• Highly Proficiency in one Python, C, or C++
• Experience with ML frameworks such as TensorFlow, Keras, and PyTorch
• Understanding of computer architecture principles.

Nice-to-haves

• Deep experience implementing LLM systems for specific hardware targets
• Multi-project experience in computer vision, audio processing, and sensor fusion
• Evidence of creativity and innovation in previous projects.