1 to 25 of 57 Distributed Computing Jobs in London

platforms, services, and data infrastructure that enable quant teams to build and operate investment analytics. This role combines strong Python engineering, data engineering, and distributed computing expertise with close partnership across both quant and technology organizations. What you can expectDesign and develop platform capabilities, services, and tooling using … Python. Build and support data platforms, quantitative libraries, distributed computing infrastructure, and shared services used by QMS researchers and investment teams. Partner closely with quantitative researchers and technology teams to align platform capabilities with business needs. Contribute to architecture, code reviews, testing, performance optimization, and operational excellence. Drive ...

filing and auditing. Experience in applying theoretical foundations of computer science, including computer system architecture, system engineering, and programming Hands-on experience in distributed computing systems and architecture that may include big data, high-performance compute, engineering simulations, scientific compute, grid and cloud computing, distributed networks ...

considered for the role, it is essential that you possess exemplary academic prowess, with a 2:1 or 1st in a relevant subject (e.g. Computing Science, Maths, Physics etc.) from a leading University and accompanying demonstrable experience gained working as a Data Engineering professional. It would be highly advantageous … process and manage large volumes of data Experience designing and implementing complex data-matching, reconciliation, and entity-resolution solutions across multiple data sources Distributed computing for data intensive work such as Spark and Databricks Cloud platforms including AWS, Azure and GCP Orchestration tools like Airflow Modern DevOps practices ...

pipeline orchestration . Strong data modelling skills (Dimensional, ODS, Data Vault) and experience with data warehousing concepts. Experience working with large, complex datasets and distributed computing environments. Proficiency in SQL , version control (e.g. Git), and CI/CD pipelines . Familiarity with Agile delivery and DevOps practices (Azure ...

Azure) Experience with: o Data warehousing and lake architectures o ETL/ELT pipeline development o SQL and NoSQL databases o Distributed computing frameworks (Spark, Kinesis etc) o Software development best practices including CI/CD, TDD and version control. o Containerisation tools like Docker or Kubernetes ...

Azure (preferred), AWS, or similar cloud platforms. Experience building scalable data platforms, data pipelines, APIs, integration services, and event-driven architectures. Strong understanding of distributed computing and large-scale data processing. Experience implementing software engineering best practices including source control, code reviews, automated testing, CI/CD, DevSecOps ...

community on behalf of AWS and Amazon.- Handle a high volume of concurrent engagements and scale with the fast pace of GenAI and cloud computing - Some relevant business level technical knowledge is required, such as: database systems, core distributed computing concepts, fundamentals of cloud computing … stop you from applying. Why AWS Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products ...

Experience Proficiency in C++, Java, or C#. Experience with KDB+/q, Kafka, Kubernetes, Docker, cloud platforms (Azure, AWS, or GCP), vector databases, or distributed computing technologies. Advanced AI & Data Experience Experience deploying machine learning models in production environments. Experience building agentic workflows, MCP-based integrations, enterprise ...

community on behalf of AWS and Amazon.- Handle a high volume of concurrent engagements and scale with the fast pace of GenAI and cloud computing - Some relevant business level technical knowledge is required, such as: database systems, core distributed computing concepts, fundamentals of cloud computing … stop you from applying. Why AWS Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products ...

pipelines for both batch and real-time data processing. Apply solid understanding of data engineering concepts, including ETL/ELT processes, data transformation, and distributed computing frameworks. Implement best practises in containerisation technologies, CI/CD practises, and cloud-native application development. Utilise version control systems such ...

/TypeScript, and modern frameworksWorking knowledge of two or more common Cloud ecosystems (AWS, Azure, GCP) with expertise in at least oneDeep experience with distributed computing with Apache Spark and knowledge of Spark runtime internalsFamiliarity with CI/CD for production deploymentsWorking knowledge of MLOps, ML/ ...

Amazon Bedrock, Azure OpenAI/AI Foundry, Google Vertex AI), vector databases (e.g., Pinecone, Weaviate, Chroma, pgvector, FAISS), containerization and orchestration (Docker, Kubernetes), and distributed computing is advantageous.• Architecture Design: Ability to design end-to-end Generative and Agentic AI architectures that encompass data preprocessing, model selection ...

high-caliber technical teams in data engineering, data platforms, software engineering, or AI/ML.Technical Depth: Strong technical background capable of evaluating architectures spanning distributed computing (Apache Spark), Python/Scala, modern cloud ecosystems (AWS, Azure, GCP), CI/CD, and MLOps/GenAI frameworks.Leadership Skills: Proven ability ...

Java, C++, Python or related language- Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing- Experience in building machine learning models for business application- PhD, or a Master's degree and experience ...

signal computation, trade-decision-making and execution. Design, implement, and maintain the core systems and services to enable real time data ingestion, retrieval and distributed compute for both research and production. Oversee the ongoing operation of all components within the systems landscape to ensure resilience and detect defects … they arise. Preferred Technical SkillsExceptional programming skills in both high-level and low-level languages (Python & C++ or similar).Familiarity with modern distributed computing platforms (specifically: docker, kubernetes, ceph, mongodb & kafka).Theoretical proficiency in numerical computing, online algorithms, data structures, networking, databases, and operating systems. Familiarity with ...

Proficient in one or more OO programming languages (e.g. Java/C#) Experience with datasets used for cash equity research and trading Experience with distributed computing (e.g. Spark/Dask, Slurm/HTCondor) Experience with event-driven, asynchronous architectures and related messaging technologies (e.g. Kafka, MQ) Experience with ...

APIs. Building cloud-native platforms supporting analytical and risk workloads. Developing orchestration frameworks for batch and on-demand calculations. Managing containerised environments and distributed compute services. Implementing monitoring, observability and operational tooling. Building resilient services with fault tolerance, recovery and retry capabilities. Creating CI/CD pipelines and deployment ...

massive scale, and extend well beyond web search. We're looking for engineers who bring fresh ideas from all areas, including information retrieval, distributed computing, large-scale system design, networking and data storage, security, artificial intelligence, natural language processing, UI design and mobile; the list goes … over their attention and device habits. Android is Google's mobile operating system powering more than 3 billion devices worldwide. Android is about bringing computing to everyone in the world. We believe computing is a super power for good, enabling access to information, economic opportunity, productivity, connectivity between ...

desired business outcomes when using the AWS Cloud. We work together with customer teams and the AWS Partner Network (APN) to execute enterprise cloud computing initiatives. Our team provides assistance through a collection of offerings which help customers achieve specific outcomes related to enterprise cloud adoption. We also deliver … desired business outcomes when using the AWS Cloud. We work together with customer teams and the AWS Partner Network (APN) to execute enterprise cloud computing initiatives. Our team provides assistance to help customers achieve specific outcomes related to enterprise cloud adoption. A typical day may include working with ...

product strategy and help develop your team. Teams work all across the company, in areas such as information retrieval, artificial intelligence, natural language processing, distributed computing, large-scale system design, networking, security, data compression, user interface design; the list goes on and is growing every day. Operating with … defining consumer needs of our time. Android is Google's mobile operating system powering more than 3 billion devices worldwide. Android is about bringing computing to everyone in the world. We believe computing is a super power for good, enabling access to information, economic opportunity, productivity, connectivity between ...

stop you from applying.Why AWS Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services … achieve. Basic qualifications- Knowledge of the primary aws services (ec2, elb, rds, route53 & s3)- Experience implementing AWS services in a variety of distributed computing environments- Experience in software development, or experience managing full application stacks from the OS up through custom applications and experience in any Bigdata architecture ...

Strong proficiency in Python Extensive experience with cloud platformsExperience with: Data warehousing and lake architectures ETL/ELT pipeline development SQL and NoSQL databases Distributed computing frameworksSoftware development best practicesContainerisation toolsExperience with Infrastructure as Code toolsStrong understanding of data modelling and system architecture Knowledge of common machine learning ...

experience with kdb+/q, Spark, Kafka, dbt, Airflow, or similar technologiesExperience leading platform transformation or modernization programmesTechnical SkillsPython, Rust, SQL, API design and distributed computing. Long-horizon agentic platforms, agent memory systems, agentic RAGKubernetes, Docker, CI/CD pipelinesData engineering, orchestration, and observabilityAI/ML platforms, MLOps ...

production health and operations of our multi-rail Ethernet backend network built on MRC and RDMA technologies. You will bridge network engineering, distributed systems, hardware health, and production operations to ensure the network delivers predictable performance at extreme scale. Your mission is simple: make the network invisible to researchers … rollback rates Automated remediation coverage Time from hardware availability to production-ready capacity QualificationsMinimum Qualifications Significant experience operating large-scale datacenter or high-performance computing networks in production. Deep understanding of Ethernet, RDMA, RoCEv2, congestion control, routing, load balancing, and lossless or near-lossless network design. Experience debugging complex ...

deep semantic retrieval, and multi-modal representation learning. Technical Stack: Mastery of Python and deep learning frameworks (TensorFlow, PyTorch) alongside hands-on experience with distributed computing (Spark, Ray) and cloud infrastructure (AWS/GCP).Desired: Graph Neural Networks (GNNs): Strong experience applying GNNs, knowledge graphs, or graph embeddings ...