1 to 25 of 510 Permanent Distributed Computing Jobs in the UK

a related field, with 10+ years of experience in software architecture (including 5+ years in AI/ML systems). Proven track record of designing and implementing large-scale, distributed AI systems. Deep understanding of AI and machine learning (natural language processing, computer vision, predictive modelling). Extensive experience with cloud platforms (AWS, Google Cloud, Azure) and their AI … databases and analysis tools. Knowledge of AI model serving frameworks like TensorFlow Serving or ONNX Runtime. Experience with AI ethics and bias mitigation techniques. Familiarity with GPU acceleration and distributed computing for AI workloads. Why Join warpSpeed: Career Growth and Impact: Technical Leadership and Innovation: Lead the architectural vision for a revolutionary Application AI platform. Opportunity to solve … complex technical challenges at the intersection of AI, cloud computing, and productivity tools. Influence the direction of AI applications in daily software tools. Career Growth and Impact: Play a key role in a rapidly growing startup that's redefining productivity in the AI era. Opportunity to shape the future of work and personal productivity for millions of users. Clear More ❯

engineering Required Skills & Qualifications 5+ years of experience in data engineering roles with progressively increasing responsibility Proven experience designing and implementing complex data pipelines at scale Strong knowledge of distributed computing frameworks (Spark, Hadoop ecosystem) Experience with cloud-based data platforms (AWS, Azure, GCP) Proficiency in data orchestration tools (Airflow, Prefect, Dagster, or similar) Solid programming skills in More ❯

scripts. Familiarity with ELT (Extract, Load, Transform) processes is a plus. Big Data Technologies : Familiarity with big data frameworks such as Apache Hadoop and Apache Spark, including experience with distributed computing and data processing. Cloud Platforms: Proficient in using cloud platforms (e.g., AWS, Google Cloud Platform, Microsoft Azure) for data storage, processing, and deployment of data solutions. Data More ❯

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 ❯

Design, build and optimise machine learning models with a focus on scalability and efficiency in our application domain Transform prototype implementations to robust production-grade implementation of models Explore distributed training architectures and federated learning capacity Create analytics environments and resources in the cloud or on-premise, spanning data engineering and science Identify the best libraries, frameworks and tools … and best practices (e.g., versioning, testing, CI/CD, API design, MLOps) Building machine learning models and pipelines in Python, using common libraries and frameworks (e.g., PyTorch, MLFlow, JAX) Distributed computing frameworks (e.g., Spark, Dask) Cloud platforms (e.g., AWS, Azure, GCP) and HP computing Containerization and orchestration (Docker, Kubernetes) Ability to scope and effectively deliver projects Strong 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 ❯

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 ❯

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 ❯

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 ❯

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 ❯

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 ❯

as Python, R, MATLAB, or C++. Familiarity with cloud platforms (AWS, Azure, Google Cloud) and microservices architecture. Nice-to-Have Requirements Experience with data modeling, containerization (Docker, Kubernetes), and distributed computing (Spark, Scala). Familiarity with GraphDB, MongoDB, SQL/NoSQL, and other DBMS technologies. Understanding of system automation, protection, and diagnostics in relevant sectors. Experience with deep More ❯

data solutions. Experience with cloud-based solutions and agile methodologies like Scrum or Kanban. Nice to have skills: Experience in retail or e-commerce. Knowledge of Big Data and Distributed Computing. Familiarity with streaming technologies like Spark Structured Streaming or Apache Flink. Additional programming skills in PowerShell or Bash. Understanding of Databricks Ecosystem components. Experience with Data Observability or More ❯

problems. Design, build and optimise machine learning models with a focus on scalability and efficiency in our application domain. Transform prototype model implementations to robust and optimised implementations. Implement distributed training architectures (e.g., data parallelism, parameter server, etc.) for multi-node/multi-GPU training and explore federated learning capacity using cloud (e.g., AWS, Azure, GCP) and on-premise … or PhD in computer science, machine learning, applied statistics, mathematics, physics, engineering, software engineering, or a related field, with a record of experience in any of the following: Scientific computing; High-performance computing (CPU/GPU clusters); Parallelised/distributed training for large/foundation models. Ideally >1 years of experience in a data-driven role, with … exposure to: scaling and optimising ML models, training and serving foundation models at scale (federated learning a bonus); distributed computing frameworks (e.g., Spark, Dask) and high-performance computing frameworks (MPI, OpenMP, CUDA, Triton); cloud computing (on hyper-scaler platforms, e.g., AWS, Azure, GCP); building machine learning models and pipelines in Python, using common libraries and frameworks More ❯

with a talented team to build and deploy scalable data pipelines to aggregate, prepare, and process data for use with machine learning. Your skills span across data processing and distributed systems with a software engineering base. You are excited to collaborate with ML engineers to build generative AI features in Autodesk products. You will report to Senior Manager, Autodesk … to work remotely, in an office, or a mix of both. Responsibilities Collaborate on engineering projects for product with a diverse, global team of researchers and engineers Develop scalable distributed systems to process, filter, and deploy datasets for use with machine learning Process large, unstructured, multi-modal (text, images, 3D models, code snippets, metadata) data sources into formats suitable … such as AWS, Azure, and GCP Containerization technologies, such as Docker and Kubernetes Documenting code, architectures, and experiments Linux systems and bash terminals Preferred Qualifications Hands-on experience with: Distributed computing frameworks, such as Ray Data and Spark. Databases and/or data warehousing technologies, such as Apache Hive. Data transformation via SQL and DBT. Orchestration platforms, such More ❯

Quant and Front Office technology teams to integrate pricing models and workflow enhancements within the ACE application. There will be exposure to a wide range of technological frameworks, including distributed computing architecture. The role will involve tasks such as: Developing and maintaining the Counterparty Credit Risk applications, leveraging in-house Python and C++ model libraries. Supporting and improving More ❯

scale data pipelines, ETL processes, and data lakes using Databricks. Demonstrable experience with cloud services, all three public clouds (AWS, GCP, Azure) is beneficial. Solid understanding of Spark architecture, distributed computing, and cloud-based data engineering principles. Proficiency in programming languages such as Python or SQL. Strong leadership skills with experience managing and growing high-performing technical teams. More ❯

Extensive experience with cloud platforms (AWS, GCP, or 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 o Experience with More ❯

concepts and best practices (e.g., versioning, testing, CI/CD, API design, MLOps) Building machine learning models and pipelines in Python, using common libraries and frameworks (e.g., TensorFlow, MLFlow) Distributed computing frameworks (e.g., Spark, Dask) Cloud platforms (e.g., AWS, Azure, GCP) and HP computing Containerization and orchestration (Docker, Kubernetes) Strong problem-solving skills and the ability to More ❯

maintenance and support Collaborate with cross-function teams and demonstrate great communication skills We're excited if you have 5+ years of experience in delivery multi-tier, highly scalable, distributed web application Deep understanding in software architecture, object-oriented design principles, and data structures Extensive experience in developing microservices using Java, Python Experience in distributed computing frameworks More ❯

as operational engineering teams. Daily/Monthly Responsibilities: Build and run responsibilities for GenAI ensuring robust support folding into standard incident processes as the products mature. Help work with distributed teams across the business on how to consume AI/ML capabilities. Hands on code, build, govern, and maintain. Working as part of a scrum team, deliver high quality …/GCP Cloud Data Fusion, Microsoft Azure Machine Learning or GCP Cloud ML Engine, Azure Data Lake, Azure Databricks or GCP Cloud Dataproc. Familiarity with big data technologies and distributed computing frameworks, such as Hadoop, Spark, or Apache Flink. Experience scaling an “API-Ecosystem”, designing, and implementing “API-First” integration patterns. Experience working with authentication and authorization protocols More ❯

IaC) concepts, and cloud security best practices Proficiency in GCP services, such as Compute Engine, Cloud Storage, BigQuery, Dataflow, and Kubernetes Engine Experience working with large-scale data processing, distributed computing, or cloud-based platforms (e.g., Hadoop, Spark, AWS, Azure) is highly desirable Familiarity with ESG investing principles and market trends is a plus Excellent problem-solving, analytical More ❯

language (Python, Java, or Scala) 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 ❯

a related field, or equivalent practical experience. Proven experience as a software engineer, with at least 3 years in a technical leadership role. Strong proficiency in C#, Relational Databases, distributed computing, middleware and integration patterns. Demonstrated ability to lead and mentor a team of engineers, fostering a collaborative and productive work environment. Experience in managing complex projects, with More ❯

a related field, or equivalent practical experience. Proven experience as a software engineer, with at least 3 years in a technical leadership role. Strong proficiency in C#, Relational Databases, distributed computing, middleware and integration patterns. Demonstrated ability to lead and mentor a team of engineers, fostering a collaborative and productive work environment. Experience in managing complex projects, with More ❯