1 to 25 of 164 PyTorch Jobs in the UK

project delivery.Support technical demonstrations, bids, proofs of concept and customer workshops.QualificationsRequired SkillsStrong Python development skills with experience using AI/ML frameworks such as PyTorch, TensorFlow, Scikit-Learn and Hugging Face.Proven experience developing and deploying machine learning solutions, including deep learning, computer vision, NLP/LLMs or time-series analytics.Experience ...

principles, model interpretability, and ethical considerations. Strong interpersonal skills and team working. Active SC Clearance.DESIRABLE:Demonstrable experience with modern deep learning frameworks (e.g. PyTorch, TensorFlow), fine-tuning or distillation of LLMs (e.g., GPT, Llama, Claude, Gemini), machine learning libraries (e.g. scikit-learn, XGBoost). Experience with data storage ...

responsible AI principles, model interpretability, and ethical considerations. Strong interpersonal skills and team working. DESIRABLE: Demonstrable experience with modern deep learning frameworks (e.g. PyTorch, TensorFlow), fine-tuning or distillation of LLMs (e.g., GPT, Llama, Claude, Gemini), machine learning libraries (e.g. scikit-learn, XGBoost). Experience with data storage ...

bring experience in managing, coaching and developing junior members of a team and wider community. DESIRABLE: Demonstrable experience with modern deep learning frameworks (e.g. PyTorch, TensorFlow), fine-tuning or distillation of LLMs (e.g. GPT, Llama, Claude, Gemini), machine learning libraries (e.g. scikit-learn, XGBoost). Experience with data storage ...

VAST, NetApp) sized for training and checkpointing workloads.AI Software, MLOps & Generative AIOrchestration & containers: Kubernetes, Docker, Slurm, Run:ai or equivalent GPU scheduling platforms.ML frameworks: PyTorch and TensorFlow at a working, hands-on level.Distributed training: Horovod, DeepSpeed, Megatron-LM, or equivalent multi-node training frameworks.Inference & serving: NVIDIA Triton, vLLM, TensorRT ...

Skills & Experience: Experience in machine learning, data science, or applied AI roles. Proficiency in Python and ML libraries (Pandas, NumPy, Scikit-learn, TensorFlow, PyTorch). Strong understanding of statistics, ML algorithms, and model evaluation techniques. Experience working with cloud platforms (AWS, Azure, or GCP) and ML pipelines. Ability to analyse ...

Skills & Experience: Experience in machine learning, data science, or applied AI roles. Proficiency in Python and ML libraries (Pandas, NumPy, Scikit-learn, TensorFlow, PyTorch). Strong understanding of statistics, ML algorithms, and model evaluation techniques. Experience working with cloud platforms (AWS, Azure, or GCP) and ML pipelines. Ability to analyse ...

experience with classical NLP techniques (BERT, topic modelling, summarisation), statistical analysis, and knowledge graphs. Deep Learning: Familiarity or experience with Deep Learning (TensorFlow, PyTorch). Benefits Package and Benefits: Competitive Salary Bonus Scheme Private Healthcare Insurance 25 Days Annual Leave + Bank Holidays Up to 10 days allocated for development ...

Jira, GitHub, and GitLab.Hands-on experience building, deploying, and scaling AI/ML solutions using frameworks and platforms such as Scikit-learn, PyTorch, TensorFlow, Hugging Face, LangChain, Databricks, Spark, vector databases, cloud services (AWS/Azure), and MLOps tools including MLflow and Kubeflow.Proven ability to develop production-grade, large-scale ...

Language Model (LLM) powered solutions and generative AI applications at enterprise scale. Strong Python development skills, with experience using machine learning frameworks such as PyTorch, TensorFlow, and Scikit-learn. Deep understanding of AI Engineering, MLOps practices, and modern LLM technologies, including prompt engineering, Retrieval-Augmented Generation (RAG), AI agents ...

Bedrock, or CrewAI Experience in machine learning development, including training, evaluating, deploying, and monitoring models Experience with deep learning or NLP frameworks, such as PyTorch or Hugging Face Good understanding of software engineering principles, design patterns, and ML lifecycle practices, including MLOps or LLMOps Experience contributing to the delivery ...

implement models, optimize performance, and manage training pipelines effectively.• Technical Proficiency: Proficiency in programming languages commonly used in AI development, such as Python, TensorFlow, PyTorch, or similar tools, along with modern LLM/agent frameworks (LangChain, LangGraph, LlamaIndex, Semantic Kernel, CrewAI, AutoGen). Experience with cloud AI platforms (e.g., Amazon ...

smooth deployment and continuous improvement.Essential Skills and Experience:Python programming skills for AI/ML development.Experience with at least one major ML framework (e.g. PyTorch, TensorFlow, scikit-learn).Experience building and maintaining end-to-end ML pipelines (data ingestion, pre-processing, training, evaluation, deployment) and deployment to production environments.Understanding ...

computer vision, NLP/LLMs, multimodal AI, self-supervised learning, reinforcement learning, time-series analytics or foundation models. Experience with AI frameworks and libraries: PyTorch, TensorFlow, scikit-learn, Hugging Face Transformers; OpenCV for vision applications. Strong understanding of experimental design, statistical evaluation, benchmarking and model validation. Experiment tracking and reproducibility ...

Track record of leading ML/AI technical initiatives across multiple teams Strong experience with cloud platforms (AWS, Azure, GCP) Experience with ML frameworks (PyTorch, TensorFlow, scikit-learn) and Gen AI/Agentic frameworks (LangGraph, LangChain, VectorDBs, RAG) Understanding of responsible AI practices, including guardrails, hallucination mitigation, and output quality ...

architecture, chunking, embeddings, reranking, evaluation, and monitoring.Experience defining evaluation approaches and using evidence to guide model, architecture, and release decisions.Experience with frameworks such as PyTorch, LangChain, LangGraph, or similar technologies.Strong experience designing and operating cloud systems using AWS, Docker, Kubernetes, Terraform, and continuous integration and deployment practices.Familiarity with services such ...

least one additional platform such as Amazon Neptune, TigerGraph, Azure Cosmos DB Gremlin, ArangoDB, or JanusGraph. Graph data science: Neo4j Graph Data Science, NetworkX, PyTorch Geometric or DGL; graph embeddings, pathfinding, similarity, clustering, link prediction, node classification, anomaly detection, and GNN development. Programming and engineering: Advanced Python and SQL; APIs ...

have experience in many of the following: Hands-on experience developing and deploying ML models in Python using frameworks such as scikit-learn, XGBoost, PyTorch, or TensorFlow Strong experience with AWS ML services (SageMaker, Lambda, S3) in production environments Strong experiment design skills: hypothesis formulation, A/B testing methodology ...

have experience in many of the following: Hands-on experience developing and deploying ML models in Python using frameworks such as scikit-learn, XGBoost, PyTorch, or TensorFlow Strong experience with AWS ML services (SageMaker, Lambda, S3) in production environments Strong experiment design skills: hypothesis formulation, A/B testing methodology ...

have experience in many of the following: Hands-on experience developing and deploying ML models in Python using frameworks such as scikit-learn, XGBoost, PyTorch, or TensorFlow Strong experience with AWS ML services (SageMaker, Lambda, S3) in production environments Strong experiment design skills: hypothesis formulation, A/B testing methodology ...

communication skills. Desirable Experience Machine Learning model development and training. LLMs, transformers, RAG and Agentic AI. LangChain, LangGraph or similar AI orchestration frameworks. PyTorch, TensorFlow, Scikit-learn or Hugging Face. Vector databases, embeddings and model evaluation. NLP, Computer Vision or multimodal AI. Edge AI, AI safety, security or explainability. Experience ...

leading ML/AI technical initiatives across multiple teams \n Strong experience with cloud platforms (AWS, Azure, GCP) \n Experience with ML frameworks (PyTorch, TensorFlow, scikit-learn) and Gen AI/Agentic frameworks (LangGraph, LangChain, VectorDBs, RAG) \n Understanding of responsible AI practices, including guardrails, hallucination mitigation, and output quality ...

computer science (e.g. databases, software engineering practices, cloud computing - especially AWS) and data science (e.g. machine learning process) Excellent knowledge of Python including Pytorch, Tensorflow and SKLearn as well as initial knowledge of LangChain and RAGAS. Familiarity with CI/CD workflows is required and experience with containerisation and deployment ...

leading ML/AI technical initiatives across multiple teams \n Strong experience with cloud platforms (AWS, Azure, GCP) \n Experience with ML frameworks (PyTorch, TensorFlow, scikit-learn) and Gen AI/Agentic frameworks (LangGraph, LangChain, VectorDBs, RAG) \n Understanding of responsible AI practices, including guardrails, hallucination mitigation, and output quality ...

leading ML/AI technical initiatives across multiple teams \n Strong experience with cloud platforms (AWS, Azure, GCP) \n Experience with ML frameworks (PyTorch, TensorFlow, scikit-learn) and Gen AI/Agentic frameworks (LangGraph, LangChain, VectorDBs, RAG) \n Understanding of responsible AI practices, including guardrails, hallucination mitigation, and output quality ...