9 of 9 Remote/Hybrid Distributed Computing Jobs in England

workloads on AWS, GCP, or Azure, utilizing managed services like SageMaker or Vertex AI. Data Foundations: Strong understanding of data modeling, feature stores, and distributed computing (e.g., Spark, Dask). Qualifications & Experience Experience: 5+ years in a software or data engineering role, with at least 3 years specifically … rather than "scripts." You anticipate edge cases, data drift, and system failures before they happen. Problem Solving: A proven track record of troubleshooting complex distributed systems and optimizing resource-intensive algorithms. What We Value Reliability: You believe that a model is only as good as its uptime ...

Vault Strong programming skills in Python and SQL. Experience building scalable, production-grade data pipelines. Understanding of data modelling, data warehousing concepts, and distributed computing. Familiarity with CI/CD, version control, and DevOps practices. Nice-to-Have Experience with streaming technologies (e.g., Spark Structured Streaming, Event Hub, Kafka ...

Spring MVC, and related technologies. Database Technologies: Strong SQL skills; experience with relational databases (e.g., Oracle, SQL Server, PostgreSQL) and/or NoSQL solutions. Distributed Systems: Understanding of distributed computing concepts and technologies (e.g., microservices, caching, clustering). Testing Frameworks: Experience with JUnit, Mockito, or similar testing ...

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 ...

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 ...

complex environments. You will work closely with stakeholders to understand real-world data challenges, transform raw and unstructured data into meaningful insights, and apply distributed compute techniques to manage large-scale, high-volume datasets across batch, streaming, and real-time platforms. Key responsibilities Develop and maintain data ingestion pipelines ...

challenges, transform raw data into meaningful insights, and support analytics and reporting. This includes working with batch, streaming, real-time, and unstructured data, applying distributed compute techniques to handle large datasets efficiently. This is a hybrid role, with time split between the Manchester office and working from home. ...

Responsibilities: Create robust, flexible, and scalable machine learning tooling and infrastructure that supports research scientists in leveraging large-scale internal infrastructure (e.g., source control, distributed compute clusters, data storage). Work collaboratively as part of a multifunctional team where communication, documentation, and teamwork are highly valued. Write clean, maintainable … focus on building and maintaining scalable infrastructure. Hands-on experience with PyTorch or similar machine learning frameworks (e.g., TensorFlow). Experience working with distributed systems or high-performance compute infrastructure. 2+ years of experience working with large, complex datasets for machine learning, including data capture and annotation. Demonstrated experience ...