1 to 25 of 152 Remote/Hybrid PyTorch Jobs in England

Machine Learning Deep Learning Neural Networks Natural Language Processing (NLP) Generative AI Large Language Models (LLMs) Retrieval-Augmented Generation (RAG) Reinforcement Learning Frameworks & Technologies PyTorch TensorFlow Scikit-learn LangChain Hugging Face OpenAI and Azure OpenAI Services Vector Databases Docker Kubernetes Cloud Platforms Microsoft Azure Azure AI Services Azure Machine Learning ...

technical demonstrations, bids, proofs of concept and customer workshops. Required Skills Strong 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 ...

technical demonstrations, bids, proofs of concept and customer workshops. Required Skills Strong 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 ...

Learning, predictive modelling and applied AI, developing, evaluating and operationalising models using state-of-the-art libraries and frameworks such as scikit-learn, TensorFlow, PyTorch and XGBoost, helping tackle complex challenges including in areas like fraud prevention, credit risk management and customer personalisation. Generative AI, Large Language Models and autonomous ...

Learning, predictive modelling and applied AI, developing, evaluating and operationalising models using state-of-the-art libraries and frameworks such as scikit-learn, TensorFlow, PyTorch and XGBoost, helping tackle complex challenges including in areas like fraud prevention, credit risk management and customer personalisation. Generative AI, Large Language Models and autonomous ...

Learning, predictive modelling and applied AI, developing, evaluating and operationalising models using state-of-the-art libraries and frameworks such as scikit-learn, TensorFlow, PyTorch and XGBoost, helping tackle complex challenges including in areas like fraud prevention, credit risk management and customer personalisation. Generative AI, Large Language Models and autonomous ...

frameworks such as LangChain/LangGraph or Hugging Face. Strong Python and SQL, with working knowledge of the wider ML stack (pandas, scikit-learn, PyTorch or TensorFlow, XGBoost). Experience with cloud data and ML platforms, ideally AWS (S3, SageMaker Pipelines, Glue) and/or GCP, and MLOps practices (MLflow ...

Machine Learning Deep Learning Neural Networks Natural Language Processing (NLP) Generative AI Large Language Models (LLMs) Retrieval-Augmented Generation (RAG) Reinforcement Learning Frameworks & Technologies PyTorch TensorFlow #J-18808-Ljbffr ...

Data Science, Physics, Computer Science, or a related field, or equivalent education and industry experience. Advanced Python proficiency with Pandas, NumPy, scikit-learn, and PyTorch or TensorFlow; SQL and practical data preparation skills. Strong statistics, experimental design, hypothesis testing, ML validation, and applied classification, regression, ranking, clustering, forecasting, and anomaly ...

/CD, observability, and automated evaluation. Education: PhD in AI/ML/CS or a related field. Beneficial knowledge: Distributed model training & infra: PyTorch DDP and FSDP, Kubeflow, Slurm, Kubernetes, and a large‐scale training framework such as DeepSpeed, Megatron or TorchTitan. LLM/Agent tooling: evaluation harnesses, prompt ...

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 ...

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 ...

practices Clear communication skills and the ability to explain AI trade-offs to non-technical clients Nice to have: experience with ML fundamentals (PyTorch, Hugging Face, fine-tuning), Wagtail, or open-source contributions Degree in Computer Science, AI/ML, or a related field, or equivalent practical experience About ...

with a track record of building and maintaining production‐quality systems. Expert‐level Python experience with numerical, statistical, or ML libraries (e.g. NumPy, pandas, PyTorch, JAX, TensorFlow). Deep understanding of statistical modelling, optimisation, or machine‐learning techniques. Experience building and operating backend systems and data pipelines in a cloud ...

prompting, embeddings, retrieval-augmented generation, tool/function calling, structured outputs, and multi-step or agentic workflows Strong Python skills, including deep learning frameworks (PyTorch or TensorFlow), the Hugging Face ecosystem, and core data libraries (NumPy, Pandas, scikit-learn) Clear written and spoken communication for both technical and business audiences ...

monitoring with open telemetry and open inference. Knowledge of observability stacks, open Bonus Points Experience with AI and machine learning frameworks at scale (e.g., PyTorch, DeepSpeed, Megatron-LM, vLLM). Hands-on experience with major cloud platforms (e.g., AWS, GCP, Azure) and hybrid cloud architectures. Advanced experience with containerization (Docker ...

dimensional datasets, ensuring efficient data loading and manipulation within training pipelines, and overseeing data quality and storage optimisation. Familiarity with deep learning frameworks (e.g., PyTorch). Architecting and building an ML platform and core ML infrastructure from the ground up, ideally in a biomedical, healthcare or scientific computing domain, including ...

connect operational bottlenecks to strategic AI solutions. Software/Data Engineering: Python proficiency, API design, SQL, data integration, and ML/AI libraries (PyTorch, TensorFlow, scikit-learn, XGBoost, Hugging Face Transformers). Agentic AI Systems: Hands-on experience with agentic AI setups including LLM orchestration, tool use/function calling ...

statistical modeling, Practical experience with ML model deployment (on cloud or on-premise), Solid programming skills in Python (NumPy, pandas, scikit-learn, matplotlib, PyTorch or TensorFlow), Understanding of Windows or Linux software development platforms Good understanding of statistics and data preparation, Working knowledge of SQL and version control tools ...

developing technical teams. Strong client-facing communication skills, with the ability to engage senior stakeholders and lead technical discussions. Desirable Experience Experience with PyTorch, TensorFlow or other machine learning frameworks. Knowledge of LLM fine-tuning, model distillation and optimisation techniques. Experience with vector databases, semantic search, knowledge graphs or related ...

Experience in data and system engineering for large-scale model workflows Proven experience with deep learning frameworks and usage of DL libraries (TensorFlow/PyTorch) Fluent with at least one of the following tools: Cursor, Windsurf, Trae, Gemini CLI, Claude Code, or Codex (or similar) Experience in applying, fine‐tune ...

projects end-to-end. Hands-On & Architectural Expertise: Strong software engineering foundations across the modern AI stack: Classic ML & Stats: Classical ML techniques (TensorFlow, PyTorch, scikit-learn), forecasting, and feature engineering. Generative AI & Agents: RAG, tool-calling, orchestration, guardrails, LLM-based agentic architectures, and fine‐tuning. Cloud & MLOps: Production deployment ...

Proficiency: Strong expertise in Python and SQL. Deep familiarity with the Python data stack (pandas, NumPy, scikit-learn) and standard ML frameworks (such as PyTorch, XGBoost, or LightGBM). Engineering Rigor: Proven ability to build for production. Experience working in cloud-based environments (AWS or GCP) and familiarity with ...

simulation analysis, rare event modeling, and stochastic modeling preferred but not required. Substantial experience with Python, R, and relevant libraries (e.g., numpy, pandas, scikit, pytorch, tidyverse, caret, ggplot, etc.). Proven experience developing, refining, and monitoring NLP models. Familiarity with database management tools and techniques (e.g., SQL, Selenium, S3, Sagemaker ...