We are seeking Systems Research Engineers with a strong interest in computer systems, distributed AI infrastructure, and performance optimization. These roles are ideal for recent PhD graduates or exceptional BSc/MSc engineers looking to build research:driven engineering experience in areas such as operating systems, distributed systems, AI model serving, and machine learning infrastructure. You will work closely with senior architects on real:world projects, helping to prototype and optimize next:generation AI infrastructure.
Required Qualifications and Skills:
Bachelor's or Master's degree in Computer Science, Electrical Engineering, or related field.
Strong knowledge of distributed systems, operating systems, machine learning systems architecture, Inference serving, and AI Infrastructure.
Hands:on experience with LLM serving frameworks (e.g., vLLM, Ray Serve, TensorRT:LLM, TGI) and distributed KV cache optimization.
Proficiency in C/C++, with additional experience in Python for research prototyping.
Solid grounding in systems research methodology, distributed algorithms, and profiling tools.
Team:oriented mindset with effective technical communication skills.
Desired Qualifications and Experience:
PhD in systems, distributed computing, or large:scale AI infrastructure.
Publications in top:tier systems or ML conferences (NSDI, OSDI, EuroSys, SoCC, MLSys, NeurIPS, ICML, ICLR).
Understanding of load balancing, state management, fault tolerance, and resource scheduling in large:scale AI inference clusters.
Prior experience designing, deploying, and profiling high:performance cloud or AI infrastructure systems.