4 of 4 Distributed Computing Jobs in East London

consistent data from external APIs and ensuring seamless incorporation into existing systems. Big Data Management and Storage : Utilize PySpark for scalable processing of large datasets, implementing best practices for distributed computing. Optimize data storage and querying within a data lake environment to enhance accessibility and performance. ML R&D : Collaborate on model prototyping and development, identifying the most relevant … 3+ years of experience in applying machine learning in a commercial setting, with a track record of delivering impactful results. Extensive programming skills in Python, with a specialization in distributed computing libraries such as PySpark. Extensive experience with PyTorch (preferred) and/or TensorFlow. Hands-on experience with deploying machine learning models in production using cloud platforms, especially More ❯

Spark, PySpark, TensorFlow . Strong knowledge of LLM algorithms and training techniques . Experience deploying models in production environments. Nice to Have: Experience in GenAI/LLMs Familiarity with distributed computing tools (Hadoop, Hive, Spark). Background in banking, risk management, or capital markets . Why Join? This is a unique opportunity to work at the forefront of More ❯

scaling our operations in London. Our work environment rewards innovation, speed, and bold thinking. The role We’re hiring Senior and Staff Software Engineers to build the high-performance computing infrastructure that powers our Optical Tensor Processing Units (OTPUs). This isn’t just about scaling models—it’s about rethinking how AI workloads are executed at speed and … scale. You’ll lead the design and implementation of software systems that run distributed, low-latency inference across clusters. You’ll work closely with hardware and ML teams to optimise every layer of the stack—from model representation and execution to data movement and scheduling. Whether it’s through compiler techniques, systems-level tuning, or custom runtime design, you … large-scale scientific compute, or AI infrastructure at serious scale, we’d love to talk. Responsibilities Design and build high-performance systems for running AI/ML workloads across distributed compute clusters Optimise for ultra-low latency and real-time inference at scale—profiling, tuning, and rewriting critical systems as needed Identify and resolve performance bottlenecks across the stack More ❯

and implement high-performance C++17+ infrastructure libraries and tools. Develop ultra-low latency systems for global trading operations. Engineer core platform components: memory allocators, kernel bypass, custom RPC, and distributed compute frameworks. Optimise performance at the hardware/software boundary, including GPU acceleration and CUDA-based compute. Work on Linux kernel internals, networking stacks, and system-level debugging. Technical … kernel-level development. Deep understanding of data structures, lock-free algorithms, and low-latency systems. Familiarity with Linux internals, system calls, and performance profiling tools. Background in platform engineering, distributed systems, or high-performance computing. Preferred Background: Participation in competitive programming contests (IOI, ICPC, Codeforces, etc.). Experience in high-frequency trading, market data systems, or real-time infrastructure More ❯