1 to 25 of 47 Ray Jobs in the UK

levels; convey information clearly and create trust with stakeholders. Preferred qualifications, capabilities, and skills Experience designing/implementing pipelines using DAGs (e.g. Kubeflow, DVC, Ray) Experience of big data technologies Have constructed batch and streaming microservices exposed as REST/gRPC endpoints Experience with container orchestration tools (e.g. Kubernetes, Helm ...

levels; convey information clearly and create trust with stakeholders. Preferred qualifications, capabilities, and skills Experience designing/implementing pipelines using DAGs (e.g. Kubeflow, DVC, Ray) Experience of big data technologies Have constructed batch and streaming microservices exposed as REST/gRPC endpoints Experience with container orchestration tools (e.g. Kubernetes, Helm ...

levels; convey information clearly and create trust with stakeholders.Preferred qualifications, capabilities, and skillsExperience designing/implementing pipelines using DAGs (e.g. Kubeflow, DVC, Ray)Experience of big data technologiesHave constructed batch and streaming microservices exposed as REST/gRPC endpointsExperience with container orchestration tools (e.g. Kubernetes, Helm) Knowledge of open source ...

experience with experiment tracking and orchestration tools such as clearml, Weights & Biases, MLflow.Experience with distributed computing frameworks and large-scale data processing (e.g., Ray, Spark, Dask)Excellent communication skills to collaborate with researchers and translate research ideas into robust implementationsSelf-driven attitude with genuine curiosity about ML research developmentsComfortable working ...

experience with cloud-native ML infrastructure platforms Knowledge of vector databases (Pinecone, Weaviate, Qdrant) and embedding models Experience with model serving frameworks (vLLM, TensorRT, Ray) Experience with A/B testing and experimentation frameworks for AI features Contributions to open-source ML projects or research publications Experience with model observability ...

fieldHands-on experience with cloud-native ML infrastructure platformsKnowledge of vector databases (Pinecone, Weaviate, Qdrant) and embedding modelsExperience with model serving frameworks (vLLM, TensorRT, Ray)Experience with A/B testing and experimentation frameworks for AI featuresContributions to open-source ML projects or research publicationsExperience with model observability tools (LangSmith ...

Experience building AI agents using frameworks such as LangChain, CrewAI, LangGraph, or similar orchestration platforms Experience operating or integrating serving platforms such as KServe, Ray Serve, NVIDIA Triton Inference Server, Text Generation Inference (TGI), alongside vLLM/llm-d Familiarity with Amazon SageMaker JumpStart, SageMaker Endpoints, and Amazon Bedrock … monitoring (e.g., hallucination, toxicity, drift detection) and tracing via OpenTelemetry conventions Contributions to open-source LLM serving or inference projects (e.g., vLLM, llm-d, Ray, KServe, Triton) ABOUT US J.P. Morgan is a global leader in financial services, providing strategic advice and products to the world's most prominent corporations ...

Experience building AI agents using frameworks such as LangChain, CrewAI, LangGraph, or similar orchestration platforms Experience operating or integrating serving platforms such as KServe, Ray Serve, NVIDIA Triton Inference Server, Text Generation Inference (TGI), alongside vLLM/llm‐d Familiarity with Amazon SageMaker JumpStart, SageMaker Endpoints, and Amazon Bedrock … monitoring (e.g., hallucination, toxicity, drift detection) and tracing via OpenTelemetry conventions Contributions to open‐source LLM serving or inference projects (e.g., vLLM, llm‐d, Ray, KServe, Triton) #J-18808-Ljbffr ...

multi‐modal representation learning. Technical Stack: Mastery of Python and deep learning frameworks (TensorFlow, PyTorch) alongside hands‐on experience with distributed computing (Spark, Ray) and cloud infrastructure (AWS/GCP). Graph Neural Networks (GNNs): Strong experience applying GNNs, knowledge graphs, or graph embeddings to map complex relations between travel ...

retrieval, and multi-modal representation learning.Technical Stack: Mastery of Python and deep learning frameworks (TensorFlow, PyTorch) alongside hands-on experience with distributed computing (Spark, Ray) and cloud infrastructure (AWS/GCP).Desired:Graph Neural Networks (GNNs): Strong experience applying GNNs, knowledge graphs, or graph embeddings to map complex relations between ...

multi-modal representation learning. Technical Stack: Mastery of Python and deep learning frameworks (TensorFlow, PyTorch) alongside hands-on experience with distributed computing (Spark, Ray) and cloud infrastructure (AWS/GCP). Graph Neural Networks (GNNs): Strong experience applying GNNs, knowledge graphs, or graph embeddings to map complex relations between travel ...

propose solutions considering effort, impact, and scalability trade-offs; Nice to have: Apache Spark, Iceberg, Kafka, dbt, Scikit-Learn, XGBoost, PyTorch, MLFlow, GraphFrames, Ray, AWS S3, EMR, SageMaker, Lakeformation, Terraform, Docker, GitHub CI/CD, Knowledge Graphs, RAG, graph ML, probabilistic programming, A/B testing. Условия No conditions specified ...

experience with cloud‐native ML infrastructure platforms Knowledge of vector databases (Pinecone, Weaviate, Qdrant) and embedding models Experience with model serving frameworks (vLLM, TensorRT, Ray) Familiarity with Anaplan or similar enterprise planning platforms Experience with A/B testing and experimentation frameworks for AI features Experience with model observability tools ...

building AI agents using orchestration frameworks such as LangChain, LangGraph, CrewAI, or similar platforms Experience operating or integrating model serving platforms such as KServe, Ray Serve, or NVIDIA Triton Inference Server alongside other large language model serving stacks Familiarity with Amazon SageMaker JumpStart, SageMaker Endpoints, and Amazon Bedrock for managed … detection, toxicity filtering, and drift detection using open telemetry conventions Contributions to open-source large language model serving or inference projects, (vLLM, llm-d, Ray, KServe, Triton) ABOUT US J.P. Morgan is a global leader in financial services, providing strategic advice and products to the world's most prominent corporations ...

patternsExperience building AI agents using orchestration frameworks such as LangChain, LangGraph, CrewAI, or similar platformsExperience operating or integrating model serving platforms such as KServe, Ray Serve, or NVIDIA Triton Inference Server alongside other large language model serving stacksFamiliarity with Amazon SageMaker JumpStart, SageMaker Endpoints, and Amazon Bedrock for managed model … hallucination detection, toxicity filtering, and drift detection using open telemetry conventionsContributions to open-source large language model serving or inference projects, (vLLM, llm-d, Ray, KServe, Triton)J.P. Morgan is a global leader in financial services, providing strategic advice and products to the world’s most prominent corporations, governments, wealthy ...

strategies, and mentoring senior and mid-level engineers. Preferred: Direct open-source or production contributions to modern inference frameworks (e.g., vLLM, Triton, TensorRT-LLM, Ray Serve, or TorchServe). Deep experience with GPU systems engineering and hardware performance optimisation (e.g., CUDA, NCCL, RDMA, NUMA, or GPU interconnects). Direct exposure ...

building AI agents using orchestration frameworks such as LangChain, LangGraph, CrewAI, or similar platforms Experience operating or integrating model serving platforms such as KServe, Ray Serve, or NVIDIA Triton Inference Server alongside other large language model serving stacks Familiarity with Amazon SageMaker JumpStart, SageMaker Endpoints, and Amazon Bedrock for managed … detection, toxicity filtering, and drift detection using open telemetry conventions Contributions to open-source large language model serving or inference projects, (vLLM, llm-d, Ray, KServe, Triton) #J-18808-Ljbffr ...

level programming (C/C++, Rust, CUDA) Direct contributions to a major inference/serving engine or similar ML infra project (e.g. PyTorch, Ray) Strong grasp of LLM inference internals (KV caching, batching, quantisation) Experience upstreaming to active OSS communities Hardware accelerator optimisation experience (GPU/TPU/etc.) Genuine ...

scale. The day‐to‐day work combines data preprocessing, model training (PyTorch, TensorFlow), evaluation against business or research metrics, and production deployment (FastAPI, Triton, Ray) with monitoring. The role increasingly overlaps with MLOps (model deployment, monitoring, retraining infrastructure) and applied ML research, taking new techniques from papers to production. Generative ...

technologies.Strong background in AWS cloud services, high-performance computing, distributed systems, containerised environments, and infrastructure automation.Experience with workload orchestration technologies such as Slurm, Kubernetes, Ray, or equivalent distributed compute frameworks.Demonstrated success bridging research and production environments, enabling rapid experimentation while maintaining operational excellence, governance, security, and reliability.Proven ability to lead ...

documentation skillsPreferred QualificationsAdvanced degree (MSc/PhD) in Machine Learning, Computer Science, or related fieldExperience scaling machine learning training and data pipelines (e.g., using Ray or similar frameworks)Experience with cloud services and architectures (e.g. AWS, Azure)Experience with LLMs or generative AI systems (fine-tuning, prompting, evaluation)Knowledge ...

hands-on experience operating ML training and serving workflows in production environments Experience with distributed training frameworks such as PyTorch Distributed, DeepSpeed, FSDP or Ray Train Experience operating experiment tracking systems and model registry systems such as MLflow, Weights and Biases or equivalent Solid understanding of cloud infrastructure ...

Your Impact Provision and manage cloud-native AI/ML infrastructure utilising Kubernetes, Docker, and GPU orchestration frameworks (e.g., NVIDIA GPU Operator, Slurm, or Ray). Automate core platform infrastructure using Infrastructure as Code (IaC) tools like Terraform, Helm, and Ansible. Optimise GPU compute workloads, high-speed networking, and storage … Docker, Helm, KubeFlow, and service meshes (e.g., Istio). Hands-on experience with Terraform, Ansible, GitHub Actions, ArgoCD, or Jenkins. Experience with vLLM, Ray, MLflow, LangChain/LangSmith, DeepSpeed, or Hugging Face TGI. Solid background in AWS/GCP/Azure, Kubecost, and GPU cost optimisation techniques. Strong skills ...

cost-efficiency.Your ImpactProvision and manage cloud-native AI/ML infrastructure utilising Kubernetes, Docker, and GPU orchestration frameworks (e.g., NVIDIA GPU Operator, Slurm, or Ray).Automate core platform infrastructure using Infrastructure as Code (IaC) tools like Terraform, Helm, and Ansible.Optimise GPU compute workloads, high-speed networking, and storage for efficient … Kubernetes (K8s), Docker, Helm, KubeFlow, and service meshes (e.g., Istio).Hands-on experience with Terraform, Ansible, GitHub Actions, ArgoCD, or Jenkins.Experience with vLLM, Ray, MLflow, LangChain/LangSmith, DeepSpeed, or Hugging Face TGI.Solid background in AWS/GCP/Azure, Kubecost, and GPU cost optimisation techniques.Strong skills in Python, Bash ...

testable, well‐documented and maintainable code, version control and code reviews; Have experience with distributed training frameworks such as PyTorch Distributed, DeepSpeed, FSDP or Ray Train; Have experience optimising models for inference, including quantisation, distillation and pruning; Nice to have: experience with biomedical data modalities such as genomics, multi‐omics ...