Systems Research Engineer

• Designing and building distributed systems for large-scale compute workloads
• Scaling Python-based services across clusters and cloud environments
• Working on ML infrastructure / platform tooling (training, orchestration, or inference pipelines)
• Improving performance, reliability, and fault tolerance across distributed environments
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They're looking for an Nngineer with strong experience in Python-based distributed computing, strong experience with Ray Framework in particular, to help design and scale systems handling complex, high-throughput workloads., * 6-8 years of experience minimum in Systems/Software Engineering.

• Strong experience with Ray (e.g. Ray Core, Ray Serve or Ray Tune)
• Strong experience with distributed systems or parallel computing
• Solid Python skills (production-level)
• Experience with frameworks like Ray, Spark, Dask, or similar
• Exposure to Kubernetes / containerised environments

Nice to have

• Background in ML infrastructure, data platforms, or backend systems ideal
• Familiarity with PyTorch / TensorFlow in production environments
• Experience building internal platforms or developer tooling
• Cloud experience (AWS, GCP, or Azure)

Why join?

• Work on genuinely complex distributed problems at scale
• High ownership and impact in a growing team
• Opportunity to shape ML infrastructure from the ground up
• Strong engineering culture with a focus on performance and scalability

Location / Package

• Ideally London, onsite, but remote will be considered for the right fit.
• Up to circa £130k + benefits per annum (dependent on experience)

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