The Role: Senior/Staff/Principal Research/SW Engineer (ML Workloads)
The role requires you to be part of the team that helps productize the SW stack for our AI compute engine. As part of the Software team, you will be responsible for the development, enhancement, and maintenance of the development and testing infrastructure for development of next-generation AI hardware. This includes the software development repo, and the testing infrastructure for the Compiler, Kernels, and will utilize simulators, FPGAs, Emulation and the chip as test platforms. You are able to build and scale software deliverables in a tight development window. You will work with a team of compiler and ML experts to build out the testing infrastructure working closely with other software and hardware experts in the company.
Qualifications
Minimum:
- Computer Science, Engineering, Math, Physics or related degree
- MS or PhD in Computer Science, Electrical Engineering, or related fields
- Strong grasp of computer architecture, data structures, system software, and machine learning fundamentals
- Strong theoretical understanding of machine learning
- Experience implementing and optimizing ML workloads and low-level software algorithms for specialized hardware such as FPGAs, DSPs, DL accelerators.
- Experience with mapping NLP models (BERT and GPT) to accelerators and awareness of trade-offs across memory, BW and compute
- Experience with ML Models from definition to deployment including training, quantization, sparsity, model preprocessing, and deployment
- Proficient in Python development in Linux environment and using standard development tools
- Experience with deep learning frameworks (such as PyTorch, Tensorflow)
- Experience training, tuning and deploying ML models for CV (ResNet,..), NLP (BERT, GPT), and/or Recommendation Systems (DLRM)
- Experience deploying ML workloads on distributed systems
- Self-motivated team player with a strong sense of ownership and leadership
Desired:
- Research background with publication record in ML conferences such as ICML, NeurIPS, ICLR,...
- Prior startup, small team or incubation experience
- Work experience at a cloud provider or AI compute / sub-system company
- Experience implementing SIMD algorithms on vector processors
- Experience with open-source ML compiler frameworks such as MLIR