This list contains only the countries for which job offers have been published in the selected language (e.g., in the French version, only job offers written in French are displayed, and in the English version, only those in English).
We are seeking a Systems Research Engineer to accelerate our Future AI Infrastructure research area. You will bring key skills and experience in operating systems, performance, distributed systems, CPUs, GPUs, and machine learning. Good systems research happens when you build things to uncover hidden assumptions – your implementation skills are at the heart of this. You will collaborate closely with researchers to identify, design and implement proof of concept solutions to some of the hardest future problems of AI infrastructure. You will partner with product teams to help land our research in a meaningful way, accelerating delivery of our lab’s research into shipping products used by millions of people world-wide. This role is within the Research Engineering team at MSR Cambridge. Our team has broad experience spanning front-end, systems, networking and ML engineering at datacentre scale. We work across all the research areas in MSR Cambridge, deeply embedded in research projects.
Job Responsibility
Combine strengths in computer systems research, and software engineering competence to contribute to the design and prioritisation of research activities
Build prototypes of future AI systems to demonstrate research value, in some cases bringing these prototypes all the way to product-level readiness
Evaluate research prototypes and help write up results to communicate outcomes clearly
Collaborate with researchers and product teams, helping with smooth technology transfer between them
Reinforce a positive environment by applying best practices and high-quality engineering standards
Gain deep expertise in one (or more) subareas of research, and general understanding of a broad area
Contribute to academic publication of research outcomes
Proactively ensure high standards of software security over research prototypes and library supply chains
Understand and follow ethics and privacy policies relating to research processes and data handling, as appropriate
Requirements
Masters degree in Computer Science or related area, or equivalent training and experience in research
Proficient in collaborative software development in Python and lower-level languages
Experience with one or more of operating systems, performance analysis, distributed systems, CPU and GPU architecture, or machine learning systems
Experience of low-level systems and/or performance tuning trade-offs
Excellent communication skills in English, both written and spoken, including the skill to communicate technical results and justify assumptions to diverse technical audiences
Willingness and flexibility to operate in a highly agile and dynamic environment
Demonstrated ability to work within large codebases
Nice to have
Doctorate (PhD) in Computer Science or related area, or equivalent training and experience in research
Experience of cluster-based distributed data processing techniques
Experience with the internals of machine learning systems
Demonstrated experience working within a multi-disciplinary team