Вакансии и проекты на Rubrain.com

We are passionate about transforming lives through cutting-edge technology, enriching industries, communities, and the world. Our mission is to create exceptional products that drive next-generation computing experiences, serving as the foundation for data centers, artificial intelligence, PCs, gaming, and embedded systems.

At the core of our mission lies a culture of innovation. We challenge boundaries to solve some of the world's most critical problems. We are committed to execution excellence, fostering a culture of openness, humility, collaboration, and inclusivity, valuing diverse perspectives along the way.

Responsibilities:

Linux application programming
Linux device driver development
Embedded C, MMU, Cache policies
Excellent debugging skills at Kernel and user space and exposure to different debugging tools
Make files

Must have Skills:

5-8 years of experience

Proficient in C and embedded systems.
Experience in Linux driver development (PCIe/USB/Ethernet) and application development.
PCIe driver development experience.
DMA client/controller driver development experience.
Hands-on experience with Configuration Management tool like Git, Perforce.
Knowledge on PCIe, Ethernet, TCP, I2C protocols, DMA framework is a plus.
Self-motivated and interested to constantly learn and share new findings.
A quality mindset, ability for strategic thinking and a drive to always improve.
Nice to have B.tech/M.Tech in CSE/IT/ECE/EEE/E&I.

Embedded C Kernel C

Удаленно

Task: Test SDK (software development kit) by documentation, run examples, write a report on what was hard/normal/easy, give recommendations for improvement.

Requirements:

- Proficiency in Python, with a solid understanding of object-oriented programming principles.

- Experience working with Linux operating systems, advanced CLI user.

- Proficiency in Bash scripting for automation and task management.

- Experience with Git for version control and collaborative development.

- Experience with Docker for containerization and deployment of applications.

- Hands-on experience running Large Language Models (LLMs) on-premise.

- Proficiency in utilizing NVIDIA GPUs to accelerate model inference and training processes.

Preferred Qualifications:

- Experience with NVIDIA’s TensorRT-LLM or similar frameworks to optimize and deploy LLMs efficiently.

- Familiarity with Kubernetes for orchestrating containerized applications in a clustered environment.

Additional Technical Skills:

- Familiarity with machine learning frameworks such as PyTorch.

- Understanding basic modern ML and DL concepts and Neural Networks architectures.