Description

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.

Essential Job Duties and 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.

Qualifications

To perform this job successfully, an individual must be able to perform each essential duty satisfactorily. The requirements listed below are representative of the knowledge, skill, and ability required. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.

Education/Experience

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.

Preferred Qualifications

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.

Language Skills

Ability to read and interpret documents, such as policies and procedures, routine mail, contracts, and instruction manuals. Ability to compose routine reports and correspondence.
Ability to effectively communicate with persons of various social, cultural, economic, and educational backgrounds.
Exceptional presentation, verbal and written skills.
Ability to independently synthesize a point of view given many different perspectives.

Reasoning Ability

Advanced ability to analyze information, problems, situations, practices, or procedures.
Advanced ability to analyze complex technical data using qualitative and quantitative sources of information to formulate logical and objective conclusions and to recognize alternatives and their implications.
Ability to carry out instructions delivered in written, oral, or other formats in daily situations.
Ability to deal with problems involving several concrete variables in standardized situations.
Ability to make timely decisions to produce positive outcomes.

Personal Attributes

Passionate about AI and embedded systems.
Highly curious and a self-starter.
Creative and persistent in problem-solving.
Ability to work collaboratively to solve problems in a fast-paced environment.

Machine Learning Engineer

Job Type