Software Development Engineer

Key Responsibilities

• Collaborate with cross-disciplinary teams (hardware design, firmware, compiler, runtime, ML engineers) to develop software for custom ML accelerator silicon.
• Design, develop, and test software across the accelerator stack, including:
• Compiler toolchains
• Device drivers
• Runtime libraries
• Profiling tools
• Simulation frameworks
• Chip validation infrastructure
• Build scalable, high-performance systems supporting chip verification, silicon bring-up, or production ML inference/training workloads.
• Write clean, maintainable code in C, C++, Python, or Rust for systems-level and performance-critical development.
• Develop CI/CD pipelines, test automation, and tooling to accelerate hardware-software co-development.
• Participate in code reviews, contribute to technical documentation, and leverage GenAI tools.
• Demonstrate operational excellence through monitoring, debugging, and resolving issues across hardware-software integration boundaries, including on-call responsibilities.
• Stay current with emerging technologies in ML accelerators, compiler optimization, computer architecture, and cloud-scale distributed systems.

Requirements & Tech Stack

• Demonstrated experience with at least one programming language: C, C++, Python, Rust, or Java.
• Demonstrated experience with one or more of the following:
• Data structures
• Algorithm development
• Systems programming
• Object-oriented design principles

Qualifications

• Currently have, or be in the process of obtaining, a Bachelor's degree or above in Computer Science, Computer Engineering, Electrical Engineering, or related STEM field.

Preferred Qualifications

• Previous technical internship(s) or demonstrated project experience in:
• Systems software
• Hardware-adjacent development
• ML infrastructure
• Experience with one or more of the following:
• Compiler design or optimization
• Computer architecture
• Device drivers or low-level systems programming
• Hardware simulation or emulation
• ML frameworks (PyTorch, TensorFlow)
• Performance profiling and analysis
• Linux kernel or embedded systems
• AI tools for development productivity
• Cloud platforms (preferably AWS)
• Version control systems
• Strong problem-solving skills with the ability to debug across hardware-software boundaries.
• Excellent written and verbal communication skills.
• Basic understanding of the hardware development lifecycle (RTL design, verification, silicon bring-up, production deployment).
• Demonstrated ability to learn and adapt to new technologies quickly.