12 of 12 Ray Jobs in England

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 travel ...

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 ...

driven pipelines What you'll bring Strong commercial MLOps or ML engineering experience, taking models from R&D into production Distributed training frameworks (eg Ray, DeepSpeed, PyTorch Lightning) Experiment tracking and model registries (eg MLflow or similar) Model optimisation (eg ONNX, TensorRT, quantisation) Docker and containerised deployment CI/ ...

driven pipelines What you'll bring Strong commercial MLOps or ML engineering experience, taking models from R&D into production Distributed training frameworks (e.g. Ray, DeepSpeed, PyTorch Lightning) Experiment tracking and model registries (e.g. MLflow or similar) Model optimisation (e.g. ONNX, TensorRT, quantisation) Docker and containerised deployment CI/ ...

bring \n \n Strong commercial MLOps or ML engineering experience, taking models from R&D into production \n Distributed training frameworks (eg Ray, DeepSpeed, PyTorch Lightning) \n Experiment tracking and model registries (eg MLflow or similar) \n Model optimisation (eg ONNX, TensorRT, quantisation) \n Docker and containerised deployment ...

clean, testable, well-documented and maintainable code, version control, code reviews Working knowledge of distributed training frameworks such as PyTorch Distributed, DeepSpeed, FSDP or Ray Train Exposure to model optimisation techniques for inference, e.g. quantisation, distillation, pruning Preferred Qualifications Experience working with biomedical data modalities such as genomics, multi-omics ...

collaborative mindset and focus on delivering business impact. What will set you apart? Experience with distributed computing and data processing frameworks such as Ray, Dask, Apache Spark, Apache Beam, or similar technologies. Experience with event-driven architectures and messaging platforms such as Kafka, RabbitMQ, or similar technologies. Experience with modern ...

tech, recommender systems or online marketplaces would be useful, as would experience with production APIs or deploying ML models. Experience with the Ray framework would also be a plus. None of these is required for the role. Uses AI-assisted development tools, including code assistants and LLM-based copilots ...

data pipeline performance trade-offs: I/O, compute, batching, memory layoutHands-on PyTorch experience: training pipelines, data loading, preprocessingPractical distributed systems experience (Ray, DDP, or similar)Experience handling TB-scale or high-throughput data pipelinesFamiliarity with columnar formats: Arrow, Parquet, IcebergNice to HaveExposure to video or visual media pipelines ...

practical experience. Preferred QualificationsSignificant additional engineering experience, with a master's degree or equivalent practical experience, building production software and distributed systems. Experience with Ray, Kubernetes, Kueue, Volcano, or another AI-focused system for scheduling, scaling, or fault tolerance is especially relevant. Software Engineering IC5 - The typical base pay range ...

scale datasets that are unstructured or semi-structured. Proficiency in statistics and exploratory data analysis methods. Familiarity with data processing frameworks such as Spark, Ray, or Apache Beam. Ability to communicate technical findings clearly to research and product teams. Software Engineering IC4 - The typical base pay range for this role ...

camera pose estimation, and monocular SLAM pipelines tailored for resource-constrained edge hardware. Develop advanced algorithms for spatial localisation, multi-view ray triangulation, sensor fusion (IMU + Camera), and plane-fitting (e.g., RANSAC, PnP) to achieve sub-centimetre overlay accuracy and eliminate tracking drift. Translate research papers into real-time … Odometry).Strong foundation in 6-DoF pose tracking, sensor fusion (IMU + Vision), and camera calibration (intrinsic/extrinsic parameters).3D geometric computer vision: ray-plane intersections, epipolar geometry, bundle adjustment, and monocular depth estimation. High proficiency in C++ and/or Python, along with standard ML and Computer Vision ...