Senior Systems Research Engineer - Research Engineering - MSR Cambridge

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. You like getting things done. 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. Understand the relevant literature and applicable research techniques. 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. Required 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. 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.