Embedded AI/ML Systems Software Developer
21 hours ago
This role involves designing, developing and optimizing embedded software solutions for artificial intelligence (AI) and machine learning (ML) workloads.
You will be responsible for creating and maintaining Linux-based environments, writing integration libraries, and enabling containerized deployment of applications on constrained edge devices.
The ideal candidate has a strong background in AI/ML, embedded systems and software development with 3-6 years of experience.
- Linux Expertise: Configure and manage Linux environments, including kernel modules, system tuning, cross-compilation and deployment scripts.
- AI/ML Optimization and Testing: Integrate ML models into embedded systems; collaborate with data science teams to enable deployment on resource-constrained hardware.
- Low-Level Engineering: Work with C, C++ and Python to build and optimize drivers, OS-level services and low-level libraries for ML acceleration.
- Containerization: Develop, test and optimize Dockerized applications for AI/ML workloads, ensuring portability, efficiency and compliance with requirements.
- Embedded Systems Ownership: Manage and maintain Edge AI development kits, ensuring smooth workflows for simulation and testing.
- Hardware Acceleration: Leverage CUDA, cuDNN and TensorRT to accelerate workloads.
- Systems Integration: Interface with satellite payload hardware and ground systems; debug integration issues across hardware, OS and application layers.
- CI/CD for Edge: Develop pipelines for automated testing and deployment of embedded software builds.
- Documentation & Support: Maintain clear documentation of configurations, workflows and deployment practices; support partner companies in deploying our dockerized products.
- Version Control & Collaboration: Git/GitHub, code review best practices and working in distributed development teams.
About the Role: This is a hands-on software development position that requires a strong understanding of AI/ML, embedded systems and software development.
Key Responsibilities:
- Design, develop and optimize embedded software solutions for AI/ML workloads.
- Create and maintain Linux-based environments.
- Write integration libraries and enable containerized deployment of applications.
- Collaborate with data science teams to enable deployment on resource-constrained hardware.
- Work with C, C++ and Python to build and optimize drivers, OS-level services and low-level libraries for ML acceleration.
- Develop, test and optimize Dockerized applications for AI/ML workloads.
- Manage and maintain Edge AI development kits.
- Leverage CUDA, cuDNN and TensorRT to accelerate workloads.
- Interface with satellite payload hardware and ground systems.
- Debug integration issues across hardware, OS and application layers.
- Develop pipelines for automated testing and deployment of embedded software builds.
- Maintain clear documentation of configurations, workflows and deployment practices.
- Support partner companies in deploying our dockerized products.
What We Offer: A dynamic and challenging role that offers opportunities for growth and development in a rapidly evolving field.
Requirements: A strong background in AI/ML, embedded systems and software development with 3-6 years of experience.
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