26 to 47 of 47 Ray Jobs in the UK

services, data pipelines, APIs, workflow systems, or developer tools.Experience with at least one distributed data or compute system such as Spark, PySpark, Flink, Kafka, Ray, Airflow, Kubernetes, BigQuery, or similar technologies.Familiarity with ML data workflows such as feature generation, training dataset creation, batch processing, real-time data processing, model training ...

writing clean, testable, well-documented and maintainable code, version control, code reviews Experience with distributed training frameworks such as PyTorch Distributed, DeepSpeed, FSDP or Ray Train Experience optimising models for inference (e.g. quantisation, distillation, pruning) Preferred Qualifications Experience working with biomedical data modalities such as genomics, multi-omics, clinical ...

knowledge of distributed systems, operating systems, machine learning systems architecture, Inference serving, and AI Infrastructure. Hands-on experience with LLM serving frameworks (e.g., vLLM, Ray Serve, TensorRT-LLM, TGI) and distributed KV cache optimization. Proficiency in C/C++, with additional experience in Python for research prototyping. Solid grounding ...

industries where reliability and performance are mission‐critical Tech stack Backend: Python Frontend: TypeScript and React Deployment: Kubernetes Infrastructure: GCP Machine learning: PyTorch, CUDA, Ray Why Encord Competitive salary, commission, and meaningful equity in a high-growth startup Strong in-person culture — most of the team works from our London ...

long as you're open to learning, please apply. Backend: Python Frontend: TypeScript and React Deployment: Kubernetes Infrastructure: GCP Machine learning: PyTorch, CUDA, Ray Why Encord Competitive salary, commission, and meaningful equity in a high-growth startup Strong in-person culture — most of the team works from our London office ...

long as you're open to learning, please apply. Backend: Python Frontend: TypeScript and React Deployment: Kubernetes Infrastructure: GCP Machine learning: PyTorch, CUDA, Ray Why Encord Competitive salary, commission, and meaningful equity in a high-growth startup Strong in-person culture — most of the team works from our London office ...

these — as long as you're open to learning. Backend: Python Frontend: TypeScript and React Deployment: Kubernetes Infrastructure: GCP Machine learning: PyTorch, CUDA, Ray Why Encord Competitive salary, commission, and meaningful equity in a high-growth startup Strong in-person culture — most of the team works from our London office ...

long as you're open to learning, please apply. Backend: Python Frontend: TypeScript and React Deployment: Kubernetes Infrastructure: GCP Machine learning: PyTorch, CUDA, Ray Why Encord Competitive salary, commission, and meaningful equity in a high-growth startup Strong in-person culture: the team works from our London office 4+ days ...

systems. Deep familiarity with JAX internals, distributed training libraries, or custom kernels/fused ops. Experience with multi-node cluster orchestration (Slurm, Ray, Kubernetes, or similar). Comfort debugging performance issues across CUDA/NCCL, networking, IO, and data pipelines. Experience working with containerized environments (Docker, Singularity/Apptainer). ...

Experience handling time-series challenges such as timestamp precision, sequence gaps, duplicate and out-of-order events. Experience with distributed processing (Spark, Polars, Dask, Ray or similar). Experience with Kafka or similar streaming technologies. Familiarity with PostgreSQL, ClickHouse, Snowflake, Databricks, kdb+ or similar. Docker, Linux, Git and CI/ ...

Experience handling time-series challenges such as timestamp precision, sequence gaps, duplicate and out-of-order events. Experience with distributed processing (Spark, Polars, Dask, Ray or similar). Experience with Kafka or similar streaming technologies. Familiarity with PostgreSQL, ClickHouse, Snowflake, Databricks, kdb+ or similar. Docker, Linux, Git and CI/ ...

long as you're open to learning, please apply. Backend: Python Frontend: TypeScript and React Deployment: Kubernetes Infrastructure: GCP Machine learning: PyTorch, CUDA, Ray Why Encord Competitive salary, commission, and meaningful equity in a high-growth startup Strong in-person culture — most of the team works from our London office ...

optimization.Strong debugging and profiling skills.PreferredExperience with large-scale recommendation, ranking, generative AI, or foundation model systems.Experience with distributed training frameworks such as PyTorch Distributed, Ray, Tensorflow, SparkFamiliarity with GPU architectures and performance analysis tools.Experience optimizing cloud infrastructure costs across large ML workloads.Contributions to internal platforms used by multiple ML teams.Experience ...

Engineering: You are an engineer first. Deep proficiency in Python/C++, experience with low-latency inference systems, and familiarity with distributed computing frameworks (Ray, Spark, Flink). You write code that survives in production, not just notebooks. The Full ML Lifecycle: Expertise in end-to‐end system design: from ...

years of experience in a data engineeringStrong proficiency in Python and RustHands-on experience with AWS cloud, Linux, and Docker.Expertise in distributed computing frameworks (Ray, Dask, or Apache Arrow).Strong analytical skills, with the ability to handle large-scale, high-frequency data.Solid understanding of ETL pipelines, data modelling, and database ...

complex optimization problems such as ranking systems or multi‐objective decision‐making You bring hands‐on experience with PyTorch and distributed systems such as Ray or similar frameworks You understand experimentation deeply and can design reliable tests in environments with interacting metrics You are able to analyze results using approaches ...

autoencoders etc.) Extensive experience with pytorch, numpy, pandas Hands‐on experience in implementing distributed/multi‐threaded/scalable applications (incl. frameworks such as Ray, Horovod, DeepSpeed, etc.) Able to communicate technical information and ideas at all levels; convey information clearly and create trust with stakeholders. Preferred qualifications, capabilities … skills Experience designing/implementing pipelines using DAGs (e.g. Kubeflow, DVC, Ray) Experience of big data technologies (e.g. Spark, Hadoop) Have constructed batch and streaming microservices exposed as REST/gRPC endpoints Familiarity with GraphQL We recognize that our people are our strength and the diverse talents they bring ...

autoencoders etc.)Extensive experience with pytorch, numpy, pandasHands-on experience in implementing distributed/multi-threaded/scalable applications (incl. frameworks such as Ray, Horovod, DeepSpeed, etc.)Able to communicate technical information and ideas at all 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 technologies (e.g. Spark, Hadoop)Have constructed batch and streaming microservices exposed as REST/gRPC endpointsFamiliarity with GraphQL#CIBAppliedAIJ.P. Morgan is a global leader in financial services, providing strategic advice and products to the world’s most prominent ...

across Linux, networking, storage, containers, Kubernetes, distributed runtimes, and production debugging.Experience with ML serving frameworks such as vLLM, Triton Inference Server, TensorRT, TorchServe, KServe, Ray Serve, or equivalent systems.Proficiency in Python for infrastructure automation, tooling, debugging, integration, and operational workflows.Practical understanding of performance tradeoffs across batching, concurrency, memory usage … planning, procurement input, reserved capacity strategy, cloud accelerator economics, or GPU fleet cost management.Experience with distributed training frameworks such as DeepSpeed, Megatron-LM, FSDP, Ray, or equivalent systems.Experience debugging CUDA, NCCL, kernel, driver, runtime, memory, networking, or low-level performance issues.Experience with Rust, C++, Go, CUDA, or other systems languages ...

systems across cloud and edge environments. Key Skills and Requirements Strong Python/PyTorch and ML infrastructure experience Experience with distributed ML training using Ray, DeepSpeed or PyTorch Lightning Strong MLflow, model registry and ML lifecycle experience Experience with TensorRT, ONNX, quantisation and model deployment Strong Docker, CI/… SKILLS: MLOps/MLOps Engineer/ML Infrastructure/ML Platform/AI Engineer/Machine Learning/ML/Python/PyTorch/Ray/DeepSpeed/PyTorch Lightning/MLflow/TensorRT/ONNX/Docker/Kubernetes/CI/CD/GitHub Actions/Prometheus/ ...

cases and/or to improve product/system performance, quality and accuracy.Near Real-Time and Batch Inferencing: Use infrastructure like Spark and Ray to stand up inferencing services that integrate with operational/analytics workloads.ML Infrastructure: Help build a first-class machine learning platform from the ground up which … applied machine learning on real recommendations use cases (brownie points for productionised sequential learning use cases!).Experience with ML/distributed ML frameworks like Ray, Spark-MLlib, TensorFlow etc.Experience with real-time scoring/evaluation of models with low latency constraints.Great coding skills and strong software development experience ...

cases and/or to improve product/system performance, quality and accuracy. Near Real-Time and Batch Inferencing: Use infrastructure like Spark and Ray to stand up inferencing services that integrate with operational/analytics workloads. ML Infrastructure: Help build a first-class machine learning platform from the ground … machine learning on real recommendations use cases (brownie points for productionised sequential learning use cases!). Experience with ML/distributed ML frameworks like Ray, Spark-MLlib, TensorFlow etc. Experience with real-time scoring/evaluation of models with low latency constraints. Great coding skills and strong software development experience ...