Join Our Innovative Team. Our client is on a mission to transform the landscape of hardware and systems with a revolutionary software-first approach, empowering AI pioneers to reach unprecedented heights. Our initiatives cover all facets of engineering, including hardware, runtime compilers, kernel optimization, algorithm development, and software architecture.
We are seeking a dynamic Tech Lead to spearhead optimization efforts for cutting-edge AI technologies, enhancing code efficiency on specialized hardware. In this collaborative role, you will be part of a team committed to innovative problem-solving and creating high-quality products that will influence the future of AI.
Key Responsibilities: - Lead the design, improvement, and upkeep of an advanced SPU compiler.
- Propose and implement enhancements to our Intermediate Representation (IR) to keep pace with emerging machine learning model architectures.
- Develop innovative compiler passes and scheduling techniques to optimize code generation.
- Utilize state-of-the-art parallelization and partitioning methods to automate kernel generation and optimize kernel performance.
- Engage in rapid prototyping and data-driven exploration to evaluate new ideas and advancements.
- Benchmark and analyze outputs on SPU hardware to ensure maximum performance.
- Work closely with hardware and software teams to address evolving requirements from ML engineers and promote architectural advancements.
- Create tools for analyzing performance bottlenecks.
Qualifications: - Deep understanding of Computer Architecture, Microarchitecture, and Computer Science.
- Expertise in designing and optimizing algorithms tailored for AI workloads.
- Extensive experience with simulation modeling techniques.
- Familiarity with emerging trends and developments in Computer Architecture.
- Strong problem-solving and analytical skills.
- Excellent written and verbal communication skills.
- Able to work both independently and collaboratively in a remote work environment.
- Ph.D. or Master's degree in Computer Science or a related discipline.
- Experience with FPGA implementation.