{"id":2199,"date":"2026-07-01T22:51:23","date_gmt":"2026-07-01T22:51:23","guid":{"rendered":"https:\/\/coderseditor.com\/itjobs\/job\/senior-ml-systems-engineer\/"},"modified":"2026-07-01T22:51:23","modified_gmt":"2026-07-01T22:51:23","slug":"senior-ml-systems-engineer","status":"publish","type":"job_listing","link":"https:\/\/coderseditor.com\/itjobs\/job\/senior-ml-systems-engineer\/","title":{"rendered":"Senior ML Systems Engineer"},"content":{"rendered":"

Senior ML Systems Engineer Overview<\/h2>\n\n\n\n\n\n\n\n\n
Company Name<\/strong><\/td>\nIC Resources Recruitment<\/td>\n<\/tr>\n
Job Role<\/strong><\/td>\nSenior ML Systems Engineer<\/td>\n<\/tr>\n
Qualifications<\/strong><\/td>\nNot Specified<\/td>\n<\/tr>\n
Category<\/strong><\/td>\nIT Jobs<\/td>\n<\/tr>\n
Job Type<\/strong><\/td>\nFull Time<\/td>\n<\/tr>\n
Location<\/strong><\/td>\nLondon<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

This is a hands-on engineering opportunity with a well-funded, research-focused organisation working at the leading edge of large-scale machine learning infrastructure. The role is centred on deep technical problem-solving, with a strong emphasis on performance modelling, distributed systems, and understanding how real hardware behaves under ML workloads. It is suited to someone who enjoys detailed systems analysis and wants their work to directly shape architecture choices at scale.<\/p>\n

What you will be doing<\/h3>\n
    \n
  • Develop simulation models that represent compute, memory, interconnect, and communication behaviour across large-scale machine learning systems.<\/li>\n
  • Build tools that can simulate both training and inference workloads running on distributed accelerator clusters.<\/li>\n
  • Represent distributed execution behaviour, including collective operations, synchronisation, and the communication constraints that can slow systems down.<\/li>\n
  • Carry out experiments and benchmarking on live ML systems so the simulation models can be calibrated and validated against real-world results.<\/li>\n
  • Assess overall system performance, looking at throughput, latency, scaling efficiency, and the balance between performance and cost.<\/li>\n
  • Work alongside hardware, software, networking, and ML specialists, and translate your findings into clear design guidance and architecture recommendations.<\/li>\n<\/ul>\n

    What the employer is looking for<\/h3>\n
      \n
    • A master\u00e2\u0080\u0099s degree or doctorate in computer science, electrical engineering, computer engineering, or a similar field.<\/li>\n
    • Strong experience in one or more of the following areas: ML systems, distributed systems, performance engineering, or simulation.<\/li>\n
    • Demonstrable ability to analyse compute, communication, and memory characteristics in large-scale ML environments.<\/li>\n
    • Practical experience with benchmarking, profiling, and measurement of machine learning systems.<\/li>\n
    • Knowledge of distributed training methods, including data parallelism, tensor parallelism, pipeline parallelism, collectives, and synchronisation.<\/li>\n
    • Programming skills in Python, C++, or Rust.<\/li>\n<\/ul>\n

      What is offered<\/h3>\n
        \n
      • A competitive salary.<\/li>\n
      • The chance to join a highly funded organisation working on advanced ML infrastructure research.<\/li>\n
      • A role with direct technical impact, where your analysis can influence architecture decisions at scale.<\/li>\n<\/ul>\n

        How to apply<\/h3>\n

        Interested candidates are invited to apply now. For more information, the named recruiter for this position is Charles Duran, who can be contacted directly to discuss the opportunity further.<\/p>\n

        The role is based in London, England.<\/p>\n

        <\/html_description><\/p>\n\n

        Degree Requirement:<\/strong> Not Specified<\/p>\n

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