The AGI (Artificial General Intelligence) Computing Lab is dedicated to solving the complex system-level challenges posed by the growing demands of future AI/ML workloads. Our team is committed to designing and developing scalable platforms that can effectively handle the computational and memory requirements of these workloads while minimizing energy consumption and maximizing performance.
Requirements
- Experience with AI/ML compiler optimizations like tiling, vectorization, parallelization, and quantization.
- Demonstrated knowledge of computer architecture, with a focus on GPUs or AI hardware accelerators and state-of-the-art domain-specific parallel programming languages.
- Prior contributions to open-source projects in the AI/ML compiler space such as LLVM, MLIR, Triton, PyTorch Inductor, etc., is a big plus.
Responsibilities
- Contribute to the design and implementation of new DSLs, compiler passes and optimizations to improve performance, efficiency, and resource utilization for executing LLM workloads on next-generation accelerators.
- Research, develop and evaluate novel compiler-based solutions for efficiently executing emerging Generative AI models on next-generation memory-centric accelerator architectures.
- Profile computational kernels written using different DSLs and analyze/debug functional and performance bottlenecks on target hardware platforms.
- Work with cutting-edge technologies and talented professionals to prepare a novel presentation for our annual Intern Exhibition, draft novel patents and scientific publication to be submitted to top-tier conferences.
- Complete other responsibilities as assigned.
Other
- Pursuing a PhD in Computer Science, Computer Engineering or related field, with focus on AI/ML Compiler technologies and deep learning models.
- Must have at least 1 academic quarter/semester remaining.
- Prior first author publications in top-tier AI/ML conferences.
- Must be highly motivated with excellent verbal and written communication skills, and ability to thrive in a collaborative, multi-disciplinary environment.
- You’re inclusive, adapting your style to the situation and diverse global norms of our people.
- An avid learner, you approach challenges with curiosity and resilience, seeking data to help build understanding.
- You’re collaborative, building relationships, humbly offering support and openly welcoming approaches.
- Innovative and creative, you proactively explore new ideas and adapt quickly to change.
