Research Systems Engineer

Research Systems Engineer focuses on driving modular design and scalability across cpu, gpu, and npu clusters, building highly efficient serving and scheduling systems.

What the role involves

• Driving modular design and scalability across CPU, GPU, and NPU clusters, building highly efficient serving and scheduling systems.
• Scalable Model Serving Infrastructure: Develop and evaluate frameworks that enable efficient multi-tenant, low-latency, and fault-tolerant AI serving across distributed environment.
• Process it on our systems.

Skills and requirements

• This role is ideal for recent PhD graduates looking to build research-driven engineering experience in areas such as operating systems, distributed systems, AI model serving, and m.
• Proficiency in C/C++, with additional experience in Python for research prototyping.
• Prior experience designing, deploying, and profiling high-performance cloud or AI infrastructure systems.

Candidate fit

• technical judgement, safe working habits, careful diagnostics, and practical problem-solving

Additional role context

• Work closely with senior architects on real-world projects, helping to prototype and optimize next-generation AI infrastructure.
• As Systems Research Engineer: Distributed Systems Research & Development: Architect, implement, and evaluate distributed system components for emerging AI and data-centric workload.
• Research and prototype new techniques for cache sharing, data locality, and resource orchestration and scheduling within AI clusters.