Machine Learning Engineer

2 months ago

Laguna Hills, United States BrainChip Full time

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 and real-time systems, contributing to the integration of ML solutions into the Akida platform.


Essential Job Duties and Responsibilities:

  • Implementing and optimizing ML algorithms for deployment on embedded systems.
  • 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 real-time systems.
  • 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.



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.
  • Proficiency in Python, C, and C++.
  • Experience with real-time operating systems (RTOS).
  • Understanding of computer architecture principles.


Preferred Qualifications:

  • Experience in developing ML applications for embedded systems.
  • Multi-project experience in State Space Models (SSM), denoising, computer vision, audio processing, and sensor fusion.
  • Experience with ML frameworks such as TensorFlow, Keras, and PyTorch.
  • Familiarity with Docker and Git.
  • Knowledge of Scrum/Agile software development methodologies (e.g., Jira).
  • 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.


Physical Demands:

  • The physical demands described here are representative of those that must be met by an employee to successfully perform the essential functions of this job. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.


Work Environment:

  • The work environment characteristics described here are representative of those an employee encounter while performing the essential functions of this job.
  • The noise level in the work environment is often low. However, there are many times when there is a high ambient background noise of phones and multiple conversations. Must be able to screen out the background noise to concentrate on the work at hand.

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