MLIR Compiler Backend Developer

THE ROLE: COMPILER BACKEND

About us

If you are following the evolution of the leading approach in deep learning powered AI, the renaissance in NLP as well as the next disruption in computer vision, you likely know it's all about Transformer based modelsThey are powering neural nets with billions to trillions of parameters and existing silicon architectures (including the plethora of AI accelerators) are struggling to varying degrees to keep up with exploding model sizes and their performance requirements. More importantly, TCO considerations for running these models at scale are becoming a bottleneck to meet exploding demand. Hyperscalers are keen on how to gain COGS efficiencies with the trillions of AI inferences/day they are already serving, but certainly for addressing the steep demand ramp they are anticipating in the next couple of years. d-Matrix is addressing this problem head on by developing a fully digital in memory computing accelerator for AI inference that is highly optimized for the computational patterns in Transformers. The fully digital approach removes some of the difficulties of analog techniques that are most often touted in pretty much all other in-memory computing AI inference products. d-Matrix's AI inference accelerator has also been architected as a chiplet, thereby enabling both a scale-up and scale-out solution with flexible packaging options. The d-Matrix team has a stellar track record in developing and commercializing silicon at scale as senior execs at the likes of Inphi, Broadcom, and Intel. Notably, they recognized early the extremely important role of programmability and the software stack and are thoughtfully building up the team in this area even since before their Series A. The company has raised $44m in funding so far and has 70+ employees across Silicon Valley, Sydney and Bengaluru.

Why d-Matrix

We want to build a company and a culture that sustains the tests of time. We offer the candidate a very unique opportunity to express themselves and become a future leader in an industry that will have a huge influence globally. We are striving to build a culture of transparency, inclusiveness and intellectual honesty while ensuring all our team members are always learning and having fun on the journey. We have built the industry's first highly programmable in-memory computing architecture that applies to a broad class of applications from cloud to edge. The candidate will get to work on a path breaking architecture with a highly experienced team that knows what it takes to build a successful business.

The team and the role

The d-Matrix compiler team is looking for exceptional candidates to help develop the compiler backend - specifically the problem of assigning hardware resources in a spatial architecture to execute low level instructions. The successful candidate will be motivated, capable of solving algorithmic compiler problems and interested in learning intricate details of the underlining hardware and software architectures. The successful candidate will join a team of experienced compiler developers, which will be guiding the candidate for a quick ramp up in the compiler infrastructure, in order to attack the important problem of mapping low level instructions to hardware resources. We have opportunities specifically in the following areas:

- Model partitioning (pipelined, tensor, model and data parallelism), tiling, resource allocation, memory management, scheduling and optimization (for latency, bandwidth and throughput).

Qualifications

Minimum: • Bachelor's degree in relevant field. • Ability to deliver production quality code in modern C++. • Experience in modern compiler infrastructures, for example: LLVM, MLIR. • Experience in machine learning frameworks and interfaces, for example: ONNX, TensorFlow and PyTorch.• Experience in production compiler development.

Desired:• Algorithm design ability, from high level conceptual design to actual implementation.• Experience with relevant Open Source ML projects like Torch-MLIR, ONNX-MLIR, Caffe, TVM.• Passionate about thriving in a fast-paced and dynamic startup culture.