1 to 25 of 29 Remote Distributed Computing Jobs in England

in applied machine learning and a passion for platform disciplines. Hands-on experience with cloud platforms (AWS, GCP, or Azure), including large-scale ML infrastructure management. Knowledge of GPU computing for model training and serving. Experience managing containerised workloads (Docker, Kubernetes, Kubeflow, etc.) and integrating with CI/CD tools (Jenkins, GitHub Actions, GitLab CI). Familiarity with distributed computing frameworks (Spark, Ray, TensorFlow Distributed, PyTorch Distributed). Strong understanding of monitoring, logging, and observability for large-scale ML systems. Experience in cost optimisation for compute/GPU workloads. Excellent people leadership and communication skills, able to influence technical and non-technical stakeholders. Comfortable working in a fast-paced, collaborative environment with strategic and operational More ❯

in applied machine learning and a passion for platform disciplines. Hands-on experience with cloud platforms (AWS, GCP, or Azure), including large-scale ML infrastructure management. Knowledge of GPU computing for model training and serving. Experience managing containerised workloads (Docker, Kubernetes, Kubeflow, etc.) and integrating with CI/CD tools (Jenkins, GitHub Actions, GitLab CI). Familiarity with distributed computing frameworks (Spark, Ray, TensorFlow Distributed, PyTorch Distributed). Strong understanding of monitoring, logging, and observability for large-scale ML systems. Experience in cost optimisation for compute/GPU workloads. Excellent people leadership and communication skills, able to influence technical and non-technical stakeholders. Comfortable working in a fast-paced, collaborative environment with strategic and operational More ❯

in applied machine learning and a passion for platform disciplines. Hands-on experience with cloud platforms (AWS, GCP, or Azure), including large-scale ML infrastructure management. Knowledge of GPU computing for model training and serving. Experience managing containerised workloads (Docker, Kubernetes, Kubeflow, etc.) and integrating with CI/CD tools (Jenkins, GitHub Actions, GitLab CI). Familiarity with distributed computing frameworks (Spark, Ray, TensorFlow Distributed, PyTorch Distributed). Strong understanding of monitoring, logging, and observability for large-scale ML systems. Experience in cost optimisation for compute/GPU workloads. Excellent people leadership and communication skills, able to influence technical and non-technical stakeholders. Comfortable working in a fast-paced, collaborative environment with strategic and operational More ❯

in applied machine learning and a passion for platform disciplines. Hands-on experience with cloud platforms (AWS, GCP, or Azure), including large-scale ML infrastructure management. Knowledge of GPU computing for model training and serving. Experience managing containerised workloads (Docker, Kubernetes, Kubeflow, etc.) and integrating with CI/CD tools (Jenkins, GitHub Actions, GitLab CI). Familiarity with distributed computing frameworks (Spark, Ray, TensorFlow Distributed, PyTorch Distributed). Strong understanding of monitoring, logging, and observability for large-scale ML systems. Experience in cost optimisation for compute/GPU workloads. Excellent people leadership and communication skills, able to influence technical and non-technical stakeholders. Comfortable working in a fast-paced, collaborative environment with strategic and operational More ❯

in applied machine learning and a passion for platform disciplines. Hands-on experience with cloud platforms (AWS, GCP, or Azure), including large-scale ML infrastructure management. Knowledge of GPU computing for model training and serving. Experience managing containerised workloads (Docker, Kubernetes, Kubeflow, etc.) and integrating with CI/CD tools (Jenkins, GitHub Actions, GitLab CI). Familiarity with distributed computing frameworks (Spark, Ray, TensorFlow Distributed, PyTorch Distributed). Strong understanding of monitoring, logging, and observability for large-scale ML systems. Experience in cost optimisation for compute/GPU workloads. Excellent people leadership and communication skills, able to influence technical and non-technical stakeholders. Comfortable working in a fast-paced, collaborative environment with strategic and operational More ❯

in applied machine learning and a passion for platform disciplines. Hands-on experience with cloud platforms (AWS, GCP, or Azure), including large-scale ML infrastructure management. Knowledge of GPU computing for model training and serving. Experience managing containerised workloads (Docker, Kubernetes, Kubeflow, etc.) and integrating with CI/CD tools (Jenkins, GitHub Actions, GitLab CI). Familiarity with distributed computing frameworks (Spark, Ray, TensorFlow Distributed, PyTorch Distributed). Strong understanding of monitoring, logging, and observability for large-scale ML systems. Experience in cost optimisation for compute/GPU workloads. Excellent people leadership and communication skills, able to influence technical and non-technical stakeholders. Comfortable working in a fast-paced, collaborative environment with strategic and operational More ❯

in applied machine learning and a passion for platform disciplines. Hands-on experience with cloud platforms (AWS, GCP, or Azure), including large-scale ML infrastructure management. Knowledge of GPU computing for model training and serving. Experience managing containerised workloads (Docker, Kubernetes, Kubeflow, etc.) and integrating with CI/CD tools (Jenkins, GitHub Actions, GitLab CI). Familiarity with distributed computing frameworks (Spark, Ray, TensorFlow Distributed, PyTorch Distributed). Strong understanding of monitoring, logging, and observability for large-scale ML systems. Experience in cost optimisation for compute/GPU workloads. Excellent people leadership and communication skills, able to influence technical and non-technical stakeholders. Comfortable working in a fast-paced, collaborative environment with strategic and operational More ❯

in applied machine learning and a passion for platform disciplines. Hands-on experience with cloud platforms (AWS, GCP, or Azure), including large-scale ML infrastructure management. Knowledge of GPU computing for model training and serving. Experience managing containerised workloads (Docker, Kubernetes, Kubeflow, etc.) and integrating with CI/CD tools (Jenkins, GitHub Actions, GitLab CI). Familiarity with distributed computing frameworks (Spark, Ray, TensorFlow Distributed, PyTorch Distributed). Strong understanding of monitoring, logging, and observability for large-scale ML systems. Experience in cost optimisation for compute/GPU workloads. Excellent people leadership and communication skills, able to influence technical and non-technical stakeholders. Comfortable working in a fast-paced, collaborative environment with strategic and operational More ❯

in applied machine learning and a passion for platform disciplines. Hands-on experience with cloud platforms (AWS, GCP, or Azure), including large-scale ML infrastructure management. Knowledge of GPU computing for model training and serving. Experience managing containerised workloads (Docker, Kubernetes, Kubeflow, etc.) and integrating with CI/CD tools (Jenkins, GitHub Actions, GitLab CI). Familiarity with distributed computing frameworks (Spark, Ray, TensorFlow Distributed, PyTorch Distributed). Strong understanding of monitoring, logging, and observability for large-scale ML systems. Experience in cost optimisation for compute/GPU workloads. Excellent people leadership and communication skills, able to influence technical and non-technical stakeholders. Comfortable working in a fast-paced, collaborative environment with strategic and operational More ❯

in applied machine learning and a passion for platform disciplines. Hands-on experience with cloud platforms (AWS, GCP, or Azure), including large-scale ML infrastructure management. Knowledge of GPU computing for model training and serving. Experience managing containerised workloads (Docker, Kubernetes, Kubeflow, etc.) and integrating with CI/CD tools (Jenkins, GitHub Actions, GitLab CI). Familiarity with distributed computing frameworks (Spark, Ray, TensorFlow Distributed, PyTorch Distributed). Strong understanding of monitoring, logging, and observability for large-scale ML systems. Experience in cost optimisation for compute/GPU workloads. Excellent people leadership and communication skills, able to influence technical and non-technical stakeholders. Comfortable working in a fast-paced, collaborative environment with strategic and operational More ❯

in applied machine learning and a passion for platform disciplines. Hands-on experience with cloud platforms (AWS, GCP, or Azure), including large-scale ML infrastructure management. Knowledge of GPU computing for model training and serving. Experience managing containerised workloads (Docker, Kubernetes, Kubeflow, etc.) and integrating with CI/CD tools (Jenkins, GitHub Actions, GitLab CI). Familiarity with distributed computing frameworks (Spark, Ray, TensorFlow Distributed, PyTorch Distributed). Strong understanding of monitoring, logging, and observability for large-scale ML systems. Experience in cost optimisation for compute/GPU workloads. Excellent people leadership and communication skills, able to influence technical and non-technical stakeholders. Comfortable working in a fast-paced, collaborative environment with strategic and operational More ❯

in applied machine learning and a passion for platform disciplines. Hands-on experience with cloud platforms (AWS, GCP, or Azure), including large-scale ML infrastructure management. Knowledge of GPU computing for model training and serving. Experience managing containerised workloads (Docker, Kubernetes, Kubeflow, etc.) and integrating with CI/CD tools (Jenkins, GitHub Actions, GitLab CI). Familiarity with distributed computing frameworks (Spark, Ray, TensorFlow Distributed, PyTorch Distributed). Strong understanding of monitoring, logging, and observability for large-scale ML systems. Experience in cost optimisation for compute/GPU workloads. Excellent people leadership and communication skills, able to influence technical and non-technical stakeholders. Comfortable working in a fast-paced, collaborative environment with strategic and operational More ❯

and transformation to ensure high-quality datasets for modelling. Proficient in programming languages such as Python, R, and SQL for data analysis and model development. Experience working with cloud computing platforms including AWS and Azure, and familiarity with distributed computing frameworks like Hadoop and Spark. Deep understanding of supply chain operations and the ability to apply data … synthesizing new algorithms and techniques Excellent communication skills Desirable Qualifications Master's or PhD level degree 5+ years of work experience in a data science role Proficient with cloud computing environments, Kubernetes, etc. Familiarity with Data Science software & platforms (e.g. Databricks) Software development experience Research and new algorithm development experience# Remote Type Hybrid Remote Skills to succeed in the More ❯

data security best practices Strong problem-solving skills, and the ability to think critically and analytically High experience in documentation and data dictionaries Knowledge of big data technologies and distributed computing frameworks such as Hadoop and Spark Excellent communication skills to effectively collaborate with cross-functional teams and present insights to business stakeholders Please can you send me More ❯

data security best practices Strong problem-solving skills, and the ability to think critically and analytically High experience in documentation and data dictionaries Knowledge of big data technologies and distributed computing frameworks such as Hadoop and Spark Excellent communication skills to effectively collaborate with cross-functional teams and present insights to business stakeholders Please can you send me More ❯

re looking for someone who; Has impactful experience deploying and maintaining ML systems in production, ideally in larger, mature organizations or teams operating at significant scale (e.g., web-scale, distributed systems, cloud-native environments). Brings expertise in MLOps: CI/CD pipelines, Docker, Kubernetes, workflow orchestration (Airflow, Prefect), and automation. Has experience across and understands the full ML … frameworks (PyTorch, TensorFlow, Scikit-learn). Is experienced with cloud platforms (ideally GCP: BigQuery, Vertex AI, Dataflow), but AWS/SageMaker or similar is also valued. Has operated in distributed computing environments, working with large datasets and parallelized processing. Can communicate technical concepts and trade-offs to both technical and non-technical audiences. Is proactive, detail-oriented, and … have any of the following Bachelor's, Master's, or PhD in Computer Science, Engineering, Data Science, or a related STEM subject (with a focus on software development or distributed systems). 3+ years of experience as an ML Engineer, MLOps Engineer, Data Engineer, or similar, in a larger-scale, production-focused environment. Hands-on with model monitoring, observability More ❯

environment. Strong proficiency in AWS services, with a focus on data-related services. Advanced skills in Python programming for data processing and automation. Experience working with large datasets and distributed computing. Previous experience supporting major customers at the early stages of projects. Strong analytical and problem-solving skills. Excellent communication and collaboration skills. Preferred Skills: Knowledge of data warehousing More ❯

environment. Strong proficiency in AWS services, with a focus on data-related services. Advanced skills in Python programming for data processing and automation. Experience working with large datasets and distributed computing. Previous experience supporting major customers at the early stages of projects. Strong analytical and problem-solving skills. Excellent communication and collaboration skills. Preferred Skills: Knowledge of data warehousing More ❯

drive innovation in training multimodal large language models (LLMs), video foundation models, and other advanced AI systems. These models will be optimized for both cloud-based deployments and edge computing environments, ensuring scalability, efficiency, and real-world applicability. You will report directly to senior leadership and play a pivotal role in shaping the company's AI strategy, from research … Scale the R&D team by recruiting top talent, fostering a collaborative culture, and implementing processes for efficient growth and knowledge sharing. Oversee scalable training pipelines, including data curation, distributed computing strategies, and hyperparameter optimization to handle massive datasets. Deliver high-quality, general-purpose models tailored to specific applications and use cases, ensuring they meet performance benchmarks for … deployments of AI models in datacenter and edge settings. Familiarity with ethical AI, bias mitigation, and regulatory compliance in model development. Strong programming skills in Python and experience with distributed systems (e.g., Kubernetes, Ray). Important information for candidates Apply only through our official channels. We do not use third-party platforms or agencies for recruitment unless clearly stated. More ❯

AAD, Machine Learning). Candidate Profile Essential Skills & Experience: Strong programming skills in C++. Solid understanding of numerical methods such as Monte Carlo simulations and optimisation algorithms. Experience with: Distributed computing and inter-process communication Multi-threading programming Microsoft Office, VC++, VBA SQL databases (Access, Oracle) Web technologies (XML, XSLT) Proven ability to work independently and as part More ❯

AAD, Machine Learning). Candidate Profile Essential Skills & Experience: Strong programming skills in C++. Solid understanding of numerical methods such as Monte Carlo simulations and optimisation algorithms. Experience with: Distributed computing and inter-process communication Multi-threading programming Microsoft Office, VC++, VBA SQL databases (Access, Oracle) Web technologies (XML, XSLT) Proven ability to work independently and as part More ❯

solutions and manage pipelines that 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, and ETL processing (e.g., NiFi). Ensure More ❯

solutions and manage pipelines that 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, and ETL processing (e.g., NiFi). Ensure More ❯

to Have Exposure to trading systems, market data, or algo/bot development Familiarity with numerical libraries (NumPy, Pandas, Numba, etc.) Understanding of version control, CI/CD, or distributed computing More ❯

to Have Exposure to trading systems, market data, or algo/bot development Familiarity with numerical libraries (NumPy, Pandas, Numba, etc.) Understanding of version control, CI/CD, or distributed computing More ❯