Software Engineer, Machine Learning - AI Application Engineering

This is a remote position.

The AI Application Engineering team’s mission is to explore, develop and help productise high-performance software and hardware technologies for AI at datacenter scale. 

We achieve this via concurrent design and optimisation of many aspects of the system such as models, algorithms, performance, and AI hardware including compute and networking. In essence, we drive the AI HW roadmap and ensure our existing and future AI workloads and software are well optimised and suited for the hardware infrastructure.

We are a diverse group of problem solvers driven by a culture of experimentation and innovation. As a Software Engineer, you will be a key member of a team of innovators, working on leading AI workloads, distributed systems, and developing architecture to enable the future of AI.

Responsibilities:

• Support projects that accelerates ML applications to best exploit modern accelerator architectures (distributed homogeneous/heterogeneous clusters, multi-core CPUs, FPGAs and GPUs), optimising training and/or inference of next generation AI workloads
  

• Work towards long-term ambitious software goals, while identifying intermediate milestones

• Develop and collaborate on software projects with other researchers and engineers across diverse disciplines.

• Collaborating with AI research scientists to accelerate the next generation of deep learning models such as Recommendation systems, Generative AI, Computer vision, NLP etc.

• Communicate progress and results.

Requirements

Qualifications:

• Strong experience in one or more of High-Performance Computing, AI/ML, performance and AI hardware including compute and networking 
  
• Experience in one or more of the following areas: machine learning, recommendation systems, pattern recognition, artificial intelligence, or related technical field
  

• Experience with developing machine learning models at scale from inception to deployment

• Experience or knowledge in developing and debugging in C/C++, Python and/or PyTorch

• PhD in Computer Science or a related STEM field.

• Strong knowledge of Computer Architecture and Distributed systems with interest in one or more of High Performance Computing, Machine Learning Models, Performance and AI hardware with emphasis on compute and networking.

• Experience working with frameworks like PyTorch, Caffe2, TensorFlow, ONNX, TensorRT

• Experience in system performance optimisations such as runtime analysis of latency, memory bandwidth, I/O access, compute utilisation analysis and associated tooling development.