3 of 3 Remote Distributed Computing Jobs in Central 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 ❯

such as Solace . Linux based systems, CI/CD pipelines, GitHub Actions, MyBatis, Maven Advanced experience with FIX Engines/Routers (Raptor, Catalyst, Chronicle, or similar tools). Distributed Systems: Experience with distributed computing , clustering , and scalability strategies . Soft Skills: Excellent communication and interpersonal skills to work effectively with both business and technology teams. Ability More ❯

Distributed Systems Engineer - Global Quant Trading Firm | Up to £400k TC A globally recognised and fast-growing quantitative trading firm are searching for a Distributed Systems Engineer to help design and optimise their distributed computing environment. You’ll be working in a highly complex and technical environment, contributing to the performance and scalability of large-scale … optimise large-scale compute-intensive workloads spanning significant numbers of nodes and concurrent tasks Design, build, and manage systems with tools like Ray and YellowDog Optimise application performance on distributed platforms Provide architectural guidance on distributed computing design and development Drive efficiency and scalability across the platform, with a focus on ML pipeline execution Company: Technology-led … HPC platform experience Job/Resource scheduling experience i.e. Yellowdog Cloud platform proficiency (any provider) Experience with large scale systems (1k+ Nodes, 10k+ tasks) Experience monitoring/troubleshooting a distributed environment Advance Ray experience for ML pipelines, tuning, distributed execution Python and Conda proficiency Docker + Kubernetes experience Knowledge of networking (TCP/IP, UDP/IP, LAN More ❯