13 of 13 Distributed Computing Jobs in Central London

PySpark, Python, SQL with atleast 5 years of experience • Working experience in Palantir Foundry platform is must • Experience designing and implementing data analytics solutions on enterprise data platforms and distributed computing (Spark/Hive/Hadoop preferred). • Proven track record of understanding and transforming customer requirements into a best-fit design and architecture. • Demonstrated experience in end … Data Science or similar discipline. • and K8S systems is a plus. Person specification: • Knowledge of Insurance Domain or Financial Industry is a strong plus. • Experienced working in multicultural globally distributed teams. • Self-starter with a positive attitude and a willingness to learn, who can manage their own workload. • Strong analytical and problem-solving skills. • Strong interpersonal and communication skills More ❯

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 ❯

Python, Java, or Scala) Extensive experience with cloud platforms (AWS, GCP, or Azure) Experience with: Data warehousing and lake architectures ETL/ELT pipeline development SQL and NoSQL databases Distributed computing frameworks (Spark, Kinesis etc) Software development best practices including CI/CD, TDD and version control. Strong understanding of data modelling and system architecture Excellent problem-solving More ❯

application platform development, web and mobile development, cloud, integration, security, etc. " Application dev experience with at least one of the cloud providers - Amazon AWS or MS Azure " Understanding of distributed computing paradigm and exposure to building highly scalable systems. " Experience with platform modernization and cloud migration projects " Expertise in Agile development methodologies like TDD, BDD, Performance/Load 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 ❯

Optimise market data pipelines and trade execution engines to improve performance and reduce latency. Ensure system reliability, scalability, and low-latency performance in a fast-paced trading environment. Utilise distributed computing and high-performance computing techniques to enhance algorithmic execution. Integrate with exchange APIs (REST/WebSocket/FIX) for real-time data processing and trading execution. … Required Qualifications: Strong understanding of quant trading logic, market structure, and execution strategies. Proficiency in C++ and Python, with experience in high-performance computing, multi-threading, and distributed systems. Experience with algorithmic trading systems in crypto, equities, FX, or derivatives at least 5 years. Knowledge of financial markets, risk management, and portfolio optimisation. Solid understanding of data structures … s, Master’s, or PhD in Computer Science, Mathematics, Engineering, or related fields. Preferred Qualifications: Experience with low-latency trading systems and high-frequency trading (HFT). Background in distributed computing, machine learning, or AI-driven trading models. Familiarity with cloud computing, Kubernetes, or containerised environments. Strong debugging, profiling, and performance optimisation skills. What We Offer: Competitive More ❯

application platform development, web and mobile development, cloud, integration, security, etc. Application dev experience with at least one of the cloud providers - Amazon AWS or MS Azure Understanding of distributed computing paradigm and exposure to building highly scalable systems. Experience with platform modernization and cloud migration projects Expertise in Agile development methodologies like TDD, BDD, Performance/Load More ❯

application platform development, web and mobile development, cloud, integration, security, etc. Application dev experience with at least one of the cloud providers - Amazon AWS or MS Azure Understanding of distributed computing paradigm and exposure to building highly scalable systems. Experience with platform modernization and cloud migration projects Expertise in Agile development methodologies like TDD, BDD, Performance/Load More ❯

and monitoring in production systems Experience with cloud platforms (GCP, AWS or Azure), especially managed ML services like SageMaker or Vertex AI Proficiency in SQL and working knowledge of distributed computing tools like Spark or Dask Nice to Have: Experience with natural language processing (NLP) e.g., using LLMs, transformers, text classification Familiarity with Graph ML (e.g., for customer More ❯

Distributed Computing Application Engineer - Systematic Hedge Fund - London Our client, a leading systematic hedge fund, is seeking a Distributed Computing Application Engineer to join their London-based team. This role involves collaborating across multiple business units to architect and optimise large-scale, compute-intensive work flows spanning global locations. You will work with cutting-edge platforms … such as Ray and YellowDog, driving the integration and support of distributed computing solutions to enhance performance and scalability in complex environments. Key Responsibilities: Partner with business teams to embed distributed computing into core workflows. Optimise applications for high performance on distributed platforms. Provide architectural and technical leadership in the design and development of distributed systems. Design, implement, and manage distributed computing solutions using Ray and YellowDog. Required Skills & Experience: Bachelor's degree in Computer Science, Engineering, or a related field. Deep understanding of loosely and tightly coupled workloads. Hands-on experience with HPC platforms and job/resource scheduling. Proficiency in cloud platforms such as AWS, Azure, or Google Cloud Platform 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 ❯

solutions at the intersection of quant finance and advanced engineering. Responsibilities Architect and build a next-gen macro analytics platform in modern C++, optimised for performance and scale. Develop distributed systems and Monte Carlo engines for real-time pricing and risk in cloud and multi-core environments. Collaborate with quants and traders to productionize models and integrate analytics into … technical foundation: Expert in modern C++ (17/20), solid Python skills, and experience with Excel integration. Quant & systems expertise: Background in quantitative disciplines, with hands-on experience in distributed computing, performance optimisation, and cloud-native deployment (Docker/Kubernetes). Leadership & domain knowledge: Proven team leadership, strong grasp of derivatives and macro products (e.g., Rates, FX), and 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 ❯