24 of 24 Remote Distributed Computing Jobs in England

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 ❯

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 ❯

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 ❯

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 ❯

orchestration (Kubernetes). Excellent problem-solving skills and ability to work independently in a fast-paced environment. Desirable: Experience with NLP, computer vision, or time-series forecasting. Familiarity with distributed computing frameworks (Spark, Ray). Experience with MLOps and model governance practices. Previous contract experience in a similar ML engineering role. Contract Details Duration: 6–12 months (extension More ❯

orchestration (Kubernetes). Excellent problem-solving skills and ability to work independently in a fast-paced environment. Desirable: Experience with NLP, computer vision, or time-series forecasting. Familiarity with distributed computing frameworks (Spark, Ray). Experience with MLOps and model governance practices. Previous contract experience in a similar ML engineering role. Contract Details Duration: 6–12 months (extension More ❯

orchestration (Kubernetes). Excellent problem-solving skills and ability to work independently in a fast-paced environment. Desirable: Experience with NLP, computer vision, or time-series forecasting. Familiarity with distributed computing frameworks (Spark, Ray). Experience with MLOps and model governance practices. Previous contract experience in a similar ML engineering role. Contract Details Duration: 6–12 months (extension More ❯

orchestration (Kubernetes). Excellent problem-solving skills and ability to work independently in a fast-paced environment. Desirable: Experience with NLP, computer vision, or time-series forecasting. Familiarity with distributed computing frameworks (Spark, Ray). Experience with MLOps and model governance practices. Previous contract experience in a similar ML engineering role. Contract Details Duration: 6–12 months (extension More ❯

orchestration (Kubernetes). Excellent problem-solving skills and ability to work independently in a fast-paced environment. Desirable: Experience with NLP, computer vision, or time-series forecasting. Familiarity with distributed computing frameworks (Spark, Ray). Experience with MLOps and model governance practices. Previous contract experience in a similar ML engineering role. Contract Details Duration: 6–12 months (extension More ❯

the ability to interact effectively with both technical and trading stakeholders. Desirable: Previous front-office or systematic trading desk experience. Familiarity with modern MLOps (Docker, Kubernetes, MLflow, Airflow) and distributed computing (Spark, Ray). Experience with alpha signal generation, regime detection, or portfolio optimization. Exposure to alternative/ESG datasets, macroeconomic indicators, and sentiment analysis. More ❯

the ability to interact effectively with both technical and trading stakeholders. Desirable: Previous front-office or systematic trading desk experience. Familiarity with modern MLOps (Docker, Kubernetes, MLflow, Airflow) and distributed computing (Spark, Ray). Experience with alpha signal generation, regime detection, or portfolio optimization. Exposure to alternative/ESG datasets, macroeconomic indicators, and sentiment analysis. More ❯

the ability to interact effectively with both technical and trading stakeholders. Desirable: Previous front-office or systematic trading desk experience. Familiarity with modern MLOps (Docker, Kubernetes, MLflow, Airflow) and distributed computing (Spark, Ray). Experience with alpha signal generation, regime detection, or portfolio optimization. Exposure to alternative/ESG datasets, macroeconomic indicators, and sentiment analysis. More ❯

the ability to interact effectively with both technical and trading stakeholders. Desirable: Previous front-office or systematic trading desk experience. Familiarity with modern MLOps (Docker, Kubernetes, MLflow, Airflow) and distributed computing (Spark, Ray). Experience with alpha signal generation, regime detection, or portfolio optimization. Exposure to alternative/ESG datasets, macroeconomic indicators, and sentiment analysis. More ❯

the ability to interact effectively with both technical and trading stakeholders. Desirable: Previous front-office or systematic trading desk experience. Familiarity with modern MLOps (Docker, Kubernetes, MLflow, Airflow) and distributed computing (Spark, Ray). Experience with alpha signal generation, regime detection, or portfolio optimization. Exposure to alternative/ESG datasets, macroeconomic indicators, and sentiment analysis. 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 ❯

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 ❯

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 ❯

environment, perfect for someone early in their infrastructure career looking to develop in a world-class engineering team. As a Junior Systems Specialist, you’ll: Help manage and scale distributed compute and petabyte-scale storage systems Install, manage, and monitor Linux (RHEL-based) environments Troubleshoot hardware and software issues across the full stack Build tools and automation scripts using More ❯

environment, perfect for someone early in their infrastructure career looking to develop in a world-class engineering team. As a Junior Systems Specialist, you’ll: Help manage and scale distributed compute and petabyte-scale storage systems Install, manage, and monitor Linux (RHEL-based) environments Troubleshoot hardware and software issues across the full stack Build tools and automation scripts using More ❯

environment, perfect for someone early in their infrastructure career looking to develop in a world-class engineering team. As a Junior Systems Specialist, you’ll: Help manage and scale distributed compute and petabyte-scale storage systems Install, manage, and monitor Linux (RHEL-based) environments Troubleshoot hardware and software issues across the full stack Build tools and automation scripts using More ❯

environment, perfect for someone early in their infrastructure career looking to develop in a world-class engineering team. As a Junior Systems Specialist, you’ll: Help manage and scale distributed compute and petabyte-scale storage systems Install, manage, and monitor Linux (RHEL-based) environments Troubleshoot hardware and software issues across the full stack Build tools and automation scripts using More ❯

environment, perfect for someone early in their infrastructure career looking to develop in a world-class engineering team. As a Junior Systems Specialist, you’ll: Help manage and scale distributed compute and petabyte-scale storage systems Install, manage, and monitor Linux (RHEL-based) environments Troubleshoot hardware and software issues across the full stack Build tools and automation scripts using More ❯

diverse sensory modalities (vision, audio, proprioception, LiDAR, etc.). Build scalable data pipelines for continuous ingestion, curation, weak supervision, and retraining. Partner with MLOps and infrastructure teams to enable distributed training and optimize models for real-time deployment. Contribute to shaping the next generation of embodied AI systems for safe, efficient automation. About You 3+ years of experience building … proficiency in Python and PyTorch or JAX . Hands-on experience with LLMs, VLMs , or generative models for image/video. Deep understanding of training infrastructure (streaming datasets, checkpointing, distributed compute). Strong communicator with clear experiment documentation and the ability to explain complex technical decisions. Bonus Points Experience in robotics , autonomous driving , or other embodied AI domains. Background More ❯