Senior R&D Engineer

Nordic Semiconductor•San Diego, CA

1d•$137,000•Onsite

About The Position

As a Senior R&D Engineer, you are responsible for developing and improving our products and technologies. You are recognized by other team members to be able to identify and suggest solutions to difficult technical problems.

Requirements

Master's degree in engineering or related field and at least 3 years of experience in product development, prototyping, testing and optimization.
Three years of experience in the following:
- C/C++ and Python
- Bash scripting for automation on Linux and Windows
- Zephyr OS and RTOS Systems
- Docker, containerization, and deployment tools
- Neural network frameworks like Tensorflow, TFLite, Keras for machine learning model development
- High-level machine learning frameworks and hardware acceleration to improve the efficiency of neural network execution
- Training and testing low power and low memory machine learning models for running on the edge NN HW accelerator
- Extract model data from a tensorflow lite model and optimize it for deployment on the HW accelerator
- IoT devices, wireless communication protocols (e.g., BLE, Zigbee, MQTT, etc) and communication protocols (e.g., I2C, SPI, etc.)
- Cloud platforms like AWS
- Typescript or JVM based languages
Good communication skills, with the ability to effectively communicate technical information to both technical and non-technical audiences.
Strong problem-solving and analytical skills.
Ability to work independently and as part of a team.
Good project management skills, with the ability to manage multiple projects simultaneously.
Ability to mentor and coach junior engineers.
Ability to take ownership of assigned tasks and work with minimal supervision.
Ability to collaborate effectively with team members and other departments.

Responsibilities

Develop and improve our products and technologies
Develop compiler component that translates tensor flow to hardware accelerator machine code.
Develop scripts for accessing data sets and training models.
Develop scripts to analyze performance metrics including accuracy, precision.
Analyze models and create the transformations necessary to accelerate on hardware.
Collaborate across teams and business units to integrate hardware acceleration and maximize end-use uptake.
Collaborate and be recognized as a technical expert in other departments to identify and solve technical problems.
Investigate and gain technical knowledge in potential adjacent technologies.
Participate and lead in scheduled project reviews.
Contribute to continuous improvement initiatives to improve product quality.
Mentor and coach junior engineers to help them develop their skills.
Analyze various machine learning models, identifying, and creating the necessary transformations to optimize them for hardware acceleration.
Perform profiling and tuning of machine learning models on specialized hardware.
Develop and debug hardware accelerator toolchains, compilers, and related software.