Skip to content

Systems Software Engineer – New Product
Company | Redwood Materials |
---|
Location | San Francisco, CA, USA |
---|
Salary | $140000 – $230000 |
---|
Type | Full-Time |
---|
Degrees | Bachelor’s, Master’s |
---|
Experience Level | Senior, Expert or higher |
---|
Requirements
- BS or MS in Computer Science, Electrical Engineering, or a related field and 7+ years of experience developing application software for hardware systems
- Strong proficiency in Python, Rust or Go
- Experience with Linux system administration and containerization technologies (Docker, Kubernetes)
- Experience profiling and optimizing code running on multi-core targets
- Familiarity with network protocols (TCP/IP, CoAP, MQTT, etc.)
- Experience with time series databases (e.g InfluxDB, Prometheus) and data visualization tools
- Strong knowledge of embedded systems and real-time operating systems
- Experience implementing a firmware OTA pipeline from cloud through downstream controllers
- Excellent problem-solving and debugging skills
- Strong communication and collaboration skills.
Responsibilities
- Design and implement a scalable and resilient system architecture for the site controller, leveraging containerization technologies like Docker and Kubernetes
- Research, leverage and develop on top of open-source software frameworks that are applicable to the functions supported by the site controller
- Create SIL and HIL test frameworks for integration testing of the product
- Administer a state-of-the-art CI/CD pipeline using tools such as AWS ECR
- Collaborate with firmware engineers to ensure seamless integration between the site controller and distributed microcontrollers
- Collaborate with modeling and systems engineers to implement control algorithms for the site
- Produce excellent software documentation
- Troubleshoot and resolve system issues in a timely manner
- Contribute to a collaborative, fast-paced startup culture, where every team member plays a crucial role in achieving company milestones.
Preferred Qualifications
- Experience with machine learning, adaptive control, model predictive control or other optimization techniques is a plus