London Office
Hybrid
ML Systems/Infrastructure Engineer
Oriole is seeking a talented ML Systems/Infrastructure Engineer to help co-optimize our AI/ML software stack with cutting-edge network hardware. You'll be a key contributor to a high-impact, agile team focused on integrating middleware communication libraries and modelling the performance of large-scale AI/ML workloads.
Key Responsibilities
Design and optimize custom GPU communication kernels to enhance performance and scalability across multi-node environments
Develop and maintain distributed communication frameworks for large-scale deep learning models, ensuring efficient parallelization and optimal resource utilization.
Profile, benchmark, and debug GPU applications to identify and resolve bottlenecks in communication and computation pipelines.
Collaborate closely with hardware and software teams to integrate optimized kernels with Oriole's next-generation network hardware and software stack.
Contribute to system-level architecture decisions for large-scale GPU clusters, with a focus on communication efficiency, fault tolerance, and novel architectures for advanced optical network infrastructure.
Required Skills & Experience
Proficient in C++ and Python, with a strong track record in high-performance computing or machine learning projects.
Expertise in GPU programming with CUDA, including deep knowledge of GPU memory hierarchies and kernel optimization.
Hands-on experience debugging GPU kernels using tools such as Cuda-gdb, Cuda Memcheck, NSight Systems, PTX, and SASS.
Strong understanding of communication libraries and protocols, including NCCL, NVSHMEM, OpenMPI, UCX, or custom collective communication implementations.
Familiarity with HPC networking protocols/libraries such as RoCE, Infiniband, Libibverbs, and libfabric.
Experience with distributed deep learning/MoE frameworks, including PyTorch Distributed, vLLM, or DeepEP.
Solid understanding of deploying and optimizing large-scale distributed deep learning workloads in production environments, including Linux, Kubernetes, SLURM, OpenMPI, GPU drivers, Docker, and CI/CD automation.
Locations London Office Remote status Hybrid
About Oriole Networks
Accelerating AI in a Low Carbon World – Oriole Networks is a photonic networking company, developing disruptive technologies for AI/ML and HPC networking that will revolutionise data centres.
London Office
Hybrid
ML Systems/Infrastructure Engineer
Loading application form
Work with us
Our current openings
Hiring at Oriole Networks
Perks
About us
Our locations
Test Hardware Engineers
Test Software Engineers
New Product Introduction Engineers
Data & privacy
Employee login
Candidate Connect login
Already working at Oriole Networks?
Let's recruit together and find your next colleague.