51 to 66 of 66 Ray Jobs in London

fundamentals: data structures, algorithms, networking, OS, concurrency, and system design.Experience running compute at cluster scale: job scheduling, resource management, retries, and reliability. Slurm, Kubernetes, Ray, Spark, or custom internal schedulers all count.Proven data-engineering experience: schema design, storage formats, compression, I/O trade-offs, and pipelines processing hundreds ...

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 ...

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 ...

Apart Experience building a production-grade runtime, compiler, workflow engine, distributed training system, database, debugger, or orchestration platform Meaningful contributions to systems such as Ray, Temporal, Kafka, Erlang/BEAM, PyTorch, JAX, TensorFlow, or comparable projects Strong API design judgement, open-source collaboration, and disciplined approaches to testing, versioning, compatibility ...

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). ...

distributed training or HPC 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).A ...

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 ...

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 ...

have Experience with simulators for robotics (Isaac Sim, MuJoCo etc.) Experience in RL for robotics. Experience building infrastructure for large‐scale RL (e.g. using ray). Publications at ICLR/ICML/NeurIPS or equivalent open‐source contributions. Familiarity with OpenVLA, Physical Intelligence (π) models, or similar open VLA frameworks. ...

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 ...

test infrastructure in CI/CD and managing cross-platform builds Excellent debugging instincts and clear, reproducible bug reports Experience with GPU programming or ray/path tracing concepts (nice to have) Background in computer graphics, including PBR, color management, and perceptual image metrics (nice to have) Familiarity with physics ...

Who we areArtefact is a leading global consulting firm dedicated to accelerating the adoption of data and AI. We work with a variety of businesses, from supermarket chains, to private equity firms and telecoms; including ...

Who we are Artefact is a leading global consulting firm dedicated to accelerating the adoption of data and AI. We work with a variety of businesses, from supermarket chains, to private equity firms and telecoms ...

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 ...

with Machine Learning experiment tracking and model registries using MLflow, Weights & Biases, Neptune, ClearML or a similar platform.Experience with distributed training frameworks such as Ray, DeepSpeed, Horovod or PyTorch FSDP.Hands-on experience optimising models for inference using TensorRT, ONNX Runtime, OpenVINO, quantisation or pruning.Strong Docker and containerisation skills, including multi … Nomad or other container-orchestration platforms.Airflow, Prefect, Dagster, Metaflow or similar workflow tools.Kafka, Pulsar, Redis Streams, RabbitMQ or other event-driven technologies.Triton Inference Server, Ray Serve, TorchServe, BentoML or Seldon Core.DVC, LakeFS, Delta Lake, Feast or other data-versioning and feature-store technologies.Terraform, Pulumi, CloudFormation or Ansible.GPU cluster management ...