15 of 15 Ray Jobs in the UK

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 implementations Self-driven attitude with genuine curiosity about ML research ...

manage multiple priorities in a fast-paced, dynamic environment Preferred Experience with GenAI and LLMs Proficiency with HuggingFace, Fastai, scikit-learn, XGBoost, LightGBM, or Ray Experience with hyperparameter optimization solutions Background in data engineering, MLOps, or LLMOps, with tools such as Docker and Kubernetes Familiarity with data pipeline tools Wondering ...

with practical experience in building and training reinforcement learning models. Excellent programming skills, with experience using reinforcement learning and ML frameworks (e.g. PyTorch, TensorFlow, Ray, Gym, RLLib, SB3, TRL) and MLOps tools. Solid understanding of hyperparameter optimisation techniques and strategies. Experience building machine learning platforms or tooling for industrial ...

HAVE: Hands-on experience with LLMs and Natural Language Processing (NLP) , including fine-tuning or prompt engineering. Familiarity with distributed computing or parallel processing (Ray, Spark, etc.). Experience deploying models in production environments (Docker, cloud services). Exposure to data engineering or working alongside data pipeline teams. A genuine ...

GenAI frameworks (LangChain, LlamaIndex, Haystack, or similar) Knowledge of vector databases (Pinecone, Weaviate, Qdrant) and embedding models Experience with model serving frameworks (vLLM, TensorRT, Ray) Background in forecasting, planning, or analytics applications Familiarity with Anaplan or similar enterprise planning platforms Experience with A/B testing and experimentation frameworks ...

with graph (DAG) representation, analysis, and processing using tools like NetworkX Experience with open source distributed computing tools in Python, such as Dask or Ray Proficiency in data processing, analysis, and visualization leveraging best-in-class open source tools, libraries, and frameworks Solid understanding of statistical modeling, machine learning techniques ...

TensorFlow Demonstrated ability to scale ML workflows in real-world settings (cloud, GPU clusters, distributed training) Comfortable with MLOps tooling (W&B, Ray, Docker, etc.) Familiar with modern model architectures High ownership mindset ideal for people who enjoy low-ego, fast-moving engineering teams No prior biotech experience needed ...

similar frameworks) Solid understanding of distributed systems concepts : messaging, consensus, data partitioning, fault tolerance Experience with technologies such as Kafka, Redis, gRPC, Kubernetes, Ray, or Dask Strong background in Linux environments and performance tuning A passion for clean code, automation, and technical excellence Exposure to financial data, trading systems ...

expertise in C Rust/Go for systems programming, plus Python for model integration. Strong knowledge of distributed runtimes and scheduling frameworks (e.g. Ray, Dask, MPI, or custom equivalents). Experience with GPU cluster management (CUDA, NCCL, Triton Inference Server) and performance tuning across accelerators. Solid grasp of cloud-native ...

expertise in C Rust/Go for systems programming, plus Python for model integration. Strong knowledge of distributed runtimes and scheduling frameworks (e.g. Ray, Dask, MPI, or custom equivalents). Experience with GPU cluster management (CUDA, NCCL, Triton Inference Server) and performance tuning across accelerators. Solid grasp of cloud-native ...

/CE/EE, or equivalent, in industry experience Deep knowledge of PyTorch Knowledge of model training framework (e.g. PyTorch Lightning, ray, etc.) In-depth knowledge of transformer architecture and ways to accelerate the training and inference of transformer models Experience of performing large scale distributed training of models ...

about twenty machine learning scientists. The team is supported by an ML Ops team that provides state-of-the-art tooling (including AWS, Encord, Ray, PyTorch Lightning and Weights & Biases). The Applied Science team works closely with product engineering to deploy models to serve our worldwide customer base. Position ...

Grafana, Prometheus, DataDog etc.) Understanding of DataOps, FinOps, and cost-optimised data management practices. Familiarity with distributed systems and high-throughput data processing (e.g. Ray, Dask, Spark). Experience with feature engineering, model lifecycle management, and data-driven research environments (e.g. JupyterHub). Our recruitment philosophy We value self-awareness ...

from home 1-2 days a week. About you: You have experience of engineering and supporting at least one HPC scheduler, such as YellowDog, Ray, Slurm or IBM Symphony You have a deep knowledge of Linux You have a good understanding of both loosely coupled and tightly coupled HPC workloads ...

your expertise in the domain area of the product component or the system in aggregate and at scale. Specific domains include Workload Management (Kubernetes, Ray, and so on); Cloud Development; Management & Observability Essential Skills and Experience Strong relevant programming experience Python/Go/C infrastructure-as-code scripting … executing responsibilities & duties above. Desirable Domain experience of the products under test: Containerisation (e.g. Docker), Virtualisation and Provisioning, Workload and job scheduling (e.g. Kubernetes, Ray) on high core-count machines and rack-scale installations. 5+ years experience in quality assurance/testing teams. Experience with the Atlassian suite ...