Research Scientist - Systems & AI Infrastructure

We are looking to hire several contract Research Scientists with expertise in computer systems and AI infrastructure to conduct cutting-edge research at the intersection of computer systems, machine learning, and distributed systems. These roles are ideal for recent PhD graduates seeking industrial research experience, or for exceptional B.Sc. or M.Sc. graduates looking to deepen their research skills in an industry setting. We welcome applicants with backgrounds in one or more of the following areas: operating systems, distributed systems, and machine learning systems.

Key Responsibilities:

• Rapid Prototyping: Collaborate with a multidisciplinary team to quickly develop and test proof-of-concept prototypes, validating research ideas in real-world, industrial environments.
• Performance Optimization: Perform detailed profiling and optimization of operating systems and large-scale distributed systems, leveraging a range of heterogeneous hardware (e.g., CPU, NPU) for enhanced performance.
• Research Publications: Transform research findings and innovative contributions into high-impact publications in top-tier academic journals and conferences.
• Technical Documentation: Create and maintain comprehensive technical documentation outlining research methods, design decisions, and implementation specifics to ensure reproducibility and support internal knowledge sharing.
• Stakeholder Engagement: Communicate research progress, performance insights, and key outcomes to internal stakeholders through clear and engaging presentations.

Required:

• Bachelor's or Master's degree in Computer Science or a related technical field.
• Be comfortable with research methodology.
• Have an in-depth understanding of operating systems and/or distributed systems and/or cloud computing and/or machine learning algorithms.
• Good programming skills, master of at least one language, such as C/C++.
• Good communication and teamwork skills.

Desired:

• PhD in operating systems, distributed systems, machine learning, or a related field.
• Published papers in top journals/conferences focused on systems (NSDI, EuroSys, SoCC, OSDI etc.) and/or machine learning (NeurIPS, ICML, ICLR).
• Experience in the full lifecycle of developing, deploying, and maintaining large-scale cloud production systems, demonstrating expertise in scalability, reliability, and performance optimization.