24 of 24 Distributed Computing Jobs in England

Engineer (AWS, Python, C#/C++, CFD/FEA) Oxford - 3-4 days per week in office. £45000 - £68000 + Package. - Must have a Computing/STEM Degree (2:1 or higher). - Can work in their Oxford head office 3-4 days week. - Must have experience with …/Distributed Computing and Applied/Mechanical Engineering Your new company You'll be joining a cutting-edge engineering and technology organisation that has grown rapidly in the UK, now pushing into global markets. Formed by world leading experts in science/software the business is redefining ...

high-scale technology and quantitative finance. This is an opportunity to lead the design of advanced pricing and risk platforms, including a high-performance distributed computing system used for real-time market data and trading support. As a Senior C# Software Engineer , you will collaborate directly with Trading … robust architecture and continuous innovation. Your Impact Architectural Strategy: Lead the design of technology solutions that form the bedrock of the firm’s analytics. Distributed Systems: Build and optimize scalable, high-performance systems using modern C# .NET frameworks. Best Practices: Define and uphold software engineering standards to ensure consistency ...

MLOps practices and model deployment. Data Platforms: relational and NoSQL databases, time‐series stores, cloud data services (AWS Redshift, Azure Synapse, Google BigQuery) and distributed computing frameworks. Analytics & BI: Tableau, Power BI, matplotlib/Plotly, Excel or similar tools for data storytelling. AI Ethics & Security: bias detection, explainability ...

Experience writing complex joins, stored procedures, and performing performance tuning. Big Data Concepts Foundational understanding of Big Data architecture (Data Lakes, Data Warehouses) and distributed processing concepts (e.g., MapReduce). ETL/ELT Basic knowledge of ETL principles and data modeling (star schema, snowflake schema). Version Control Practical … experience with Git (branching, merging, pull requests). Preferred Qualifications (A Plus) Experience with a distributed computing framework like Apache Spark (using PySpark). Familiarity with cloud data services ( AWS S3/Redshift, Azure Data Lake/Synapse, or Google BigQuery/Cloud Storage ). Exposure to workflow ...

scalable data platforms and integrating Generative AI capabilities into enterprise systems. Key Responsibilities Design, build and maintain scalable data pipelines using PySpark, Python and distributed computing frameworks Architect and optimise AWS-based data and AI infrastructure for secure, high-performance data processing Develop, fine-tune, benchmark and evaluate … GenAI solutions into production environments Ensure data quality, governance and operational reliability across systems Essential Skills & Experience Strong experience with PySpark and large-scale distributed data processing (ETL/ELT pipelines) Advanced SQL expertise, including schema design (star/snowflake), indexing and optimisation techniques Proven experience implementing ...

advanced analytics techniques including machine learning, optimisation and segmentation. Strong proficiency in Python, SQL and Spark SQL. Experience working with large datasets and distributed computing tools such as Azure Synapse and Snowflake. Familiarity with data transformation tools (Databricks, Azure Data Factory) and ML platforms (Azure ML, TensorFlow). ...

transform diverse data sources into valuable insights for our client’s National Security customers. You will collaborate with clients to solve complex challenges, utilising distributed computing techniques to handle large-scale, real-time, and unstructured data. Responsibilities include: Design and develop data pipelines, including ingestion, orchestration ...

transform diverse data sources into valuable insights for our client’s National Security customers. You will collaborate with clients to solve complex challenges, utilising distributed computing techniques to handle large-scale, real-time, and unstructured data. Responsibilities include: Design and develop data pipelines, including ingestion, orchestration ...

operational datasets. Proven experience delivering complex end-to-end data platforms in Azure or Fabric environments. Strong understanding of medallion architectures, Delta Lake, distributed compute and modern data engineering principles. Experience defining data engineering standards, governance and security frameworks. Ability to engage confidently with business, product and technical stakeholders. ...

Experience with production machine learning or LLM-based systems Exposure to enterprise data platforms or similar tools Frontend development experience (e.g., React) Familiarity with distributed computing frameworks (e.g., Spark) What’s on Offer Competitive compensation package, including equity Comprehensive benefits Hybrid working model Opportunity to build products ...

Desirable Skills: Experience with Microsoft Fabric, Azure Machine Learning or similar enterprise cloud platforms. Exposure to MLOps practices, lifecycle management and large-scale or distributed compute environments. Familiarity with agentic AI concepts and frameworks such as LangChain, AutoGen or CrewAI, with an interest in developing deeper expertise. ...

Your Responsibilities: Design and maintain scalable data pipelines using PySpark, Python, and distributed computing frameworks to support high‐volume data processing. Architect and optimize AWS-based data and AI infrastructure, ensuring secure, performant, and cost‐efficient ingestion, transformation, and storage. Develop, finetune, benchmark, and evaluate GenAI/… functional teams to integrate GenAI capabilities into production systems and ensure high-quality data, governance, and operational reliability Your Profile: Strong experience with PySpark, distributed data processing, and largescale ETL/ELT pipelines. Strong SQL expertise including star/snowflake schema design, indexing strategies, writing optimized queries, and implementing ...

Role GenAI Data Engineer Your responsibilities: Design and maintain scalable data pipelines using PySpark, Python, and distributed computing frameworks to support high‐volume data processing. Architect and optimize AWS-based data and AI infrastructure, ensuring secure, performant, and cost‐efficient ingestion, transformation, and storage. Develop, finetune, benchmark … into production systems and ensure high-quality data, governance, and operational reliability Your Profile Essential skills/knowledge/experience: Strong experience with PySpark, distributed data processing, and largescale ETL/ELT pipelines. Strong SQL expertise including star/snowflake schema design, indexing strategies, writing optimized queries, and implementing ...

complex production issues and operate well in a fast‐paced, high‐pressure environment. A propensity to automate manual tasks, appreciation for large‐scale, and distributed computing systems will be necessary to succeed in the role. As part of a global support team, you will provide operational and technical … response. Proficiency in at least one scripting or programming language (e.g., Python, Shell Scripting, Java, C++) for automation, tooling, and operational tasks. Experience with distributed systems design, maintenance, and troubleshooting. Knowledge of financial markets, electronic trading workflows, and the FIX protocol. Demonstrated ability to debug, optimize, and troubleshoot code ...

cloud, or software to enterprise accounts preferred Deep understanding of the architecture, design and implementation of multi‐tiered client/server and web‐based computing solutions Prior experience in targeting new prospects and converting them into clients Contribute significant portions and/or lead responses to RFPs, RFQs … RFIs Superior knowledge of current and emerging storage architectures (FC, iSCSI, NAS, OSD, SAN) Linux, NFS file systems and Linux distributed network environment Familiarity with AWS, Azure, GCP a plus Installation/configuration of distributed computing, multiprocessing, virtual memory subsystem, storage subsystems architecture, shared memory architectures, cache ...

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 ...

data flows Excellent problem solving and communication skills Technical Skills Unix/Linux SQL Python KDB Monitoring tools: Dynatrace , Splunk ITIL processes Grid/distributed computing (nice to have) Modis International Ltd acts as an employment agency for permanent recruitment and an employment business for the supply ...

trade-offs, including performance, cost, scalability, and operational excellence. Technical understanding of modern data platform architectures, including data lakes, data warehouses, lakehouse architectures, and distributed computing frameworks. Experience with enterprise-scale implementations of cloud-native data platforms such as Databricks and Snowflake. Strong knowledge of AWS data analytics ...

data warehousing platforms (Snowflake preferred). Experience implementing monitoring, logging, and alerting for production systems. Strong debugging and incident response skills for complex distributed systems. Preferred Qualifications Experience deploying models to edge or embedded devices. Background in healthcare, medical devices, or clinical data systems. Familiarity with model serving frameworks … . Experience supporting data science or ML research teams in a production context. Exposure to HIPAA compliance and healthcare security best practices. Experience with distributed compute frameworks (e.g. Apache Spark, Dask) for large-scale data processing. Experience with streaming or real-time inference architectures. What You Bring You take ...

fields. We are not a research lab, nor are we an AI agents company. We’re working at the intersection of LLMs and evolutionary computing to build self-improving systems. We’re looking for exceptionally talented engineers and researchers to join us on this epic quest Responsibilities Write SOTA … written and shipped high-performance or SOTA CUDA kernels Deep understanding of mixed precision, quantisation (INT4, INT8, FP8, MXFP4, block-scaled formats), kernel fusion, distributed computing strategies (TP, PP, CP) You've made deliberate choices about tiling, memory access patterns, warp-level primitives, and instruction scheduling ...

large-scale compute, data centre capacity, and power solutions for advanced machine learning workloads. Platforms support leading research and industry teams requiring high-performance computing at significant scale. Fast-paced environment with emphasis on ownership, execution speed, and quality. Culture centred on pragmatic problem-solving, cross-functional collaboration … full lifecycle responsibility. Role Overview: Position operating across software, infrastructure, and operations to ensure reliability, scalability, and performance of a globally distributed compute platform. Close collaboration with networking, platform engineering, and physical infrastructure teams to design and operate systems supporting high-demand computational workloads. Hands-on engineering role requiring ...

operating multi-GPU, cross-cloud platforms that enable efficient, reliable, and scalable model training. You’ll work at the intersection of DevOps, MLOps, and distributed systems, helping push the limits of real-world AI. What You’ll Do: Design, build, and operate scalable multi-GPU infrastructure across cloud environments … code and automation for provisioning, orchestration, and lifecycle management Build and evolve CI/CD pipelines for both infrastructure and ML training workflows Optimize distributed training workloads (scheduling, resource utilization, observability) Ensure high standards of reliability, scalability, security, and monitoring across systems Collaborate with ML engineers and researchers ...

multi-GPU, cross-cloud platforms, driving architecture, reliability, and performance at scale. This role sits at the intersection of DevOps, MLOps, and distributed systems, enabling cutting-edge AI in real-world environments. What You’ll Do: Lead the design and evolution of scalable multi-GPU infrastructure across cloud environments … code and automation for provisioning, orchestration, and lifecycle management Architect and improve CI/CD systems for both infrastructure and ML training workflows Optimize distributed training workloads (scheduling, resource utilization, observability) Partner with ML engineers and researchers to enable efficient experimentation and productionization Lead troubleshooting and resolution of complex ...

operating systems to automation and observability—while gaining exposure to how a world-class investment firm manages its technology infrastructure. Key Responsibilities Manage a distributed compute environment and several petabyte-scale storage systems Install, configure, and monitor RHEL-based Linux environments Troubleshoot hardware and software issues across the stack … Experience with modern software development practices (version control, agile methodologies) Familiarity with infrastructure automation and configuration management tools (Chef, Puppet, or Ansible) Exposure to distributed storage systems and related protocols Experience with observability and monitoring tools (Elasticsearch, Logstash, Kibana, Datadog, Prometheus, Grafana) Strong written and verbal communication skills Demonstrated ...