1 to 25 of 108 PyTorch Jobs in the UK excluding London

Demonstrable experience in Machine Learning, NLP, and GenAI including LLM/SLM fine-tuning and prompt development. Proficiency in Python and data libraries such as Pandas, NumPy, Scikit-learn, PyTorch/TensorFlow. Practical knowledge in SQL/NoSQL databases and API development/integration. Proven ability to analyze model performance and optimize for accuracy, efficiency, and scalability. Exposure to prominent More ❯

and AI Required Skills & Qualifications: Strong experience in C#, .NET Framework, .NET Core/6/7, ASP.NET Experience with AI/ML frameworks such as: ML.NET TensorFlow/PyTorch (for integration with .NET) Azure Cognitive Services/OpenAI/AI APIs Knowledge of RESTful APIs , microservices, and cloud platforms (Azure, AWS, or GCP) Familiarity with SQL and NoSQL databases More ❯

and AI Required Skills & Qualifications: Strong experience in C#, .NET Framework, .NET Core/6/7, ASP.NET Experience with AI/ML frameworks such as: ML.NET TensorFlow/PyTorch (for integration with .NET) Azure Cognitive Services/OpenAI/AI APIs Knowledge of RESTful APIs , microservices, and cloud platforms (Azure, AWS, or GCP) Familiarity with SQL and NoSQL databases More ❯

and AI Required Skills & Qualifications: Strong experience in C#, .NET Framework, .NET Core/6/7, ASP.NET Experience with AI/ML frameworks such as: ML.NET TensorFlow/PyTorch (for integration with .NET) Azure Cognitive Services/OpenAI/AI APIs Knowledge of RESTful APIs , microservices, and cloud platforms (Azure, AWS, or GCP) Familiarity with SQL and NoSQL databases More ❯

Storyteller makes technical findings accessible and impactful. Connector collaborates seamlessly across data, commercial, and ops teams. Hard Skills Required Programming & Data Science: Python (Pandas, NumPy, scikit-learn, TensorFlow or PyTorch) essential; R (desirable) Data Engineering & Cloud: Advanced SQL, ETL/ELT tools (Airflow/dbt), AWS/Azure/GCP Machine Learning & AI: Classification, regression, clustering, forecasting; NLP (text mining More ❯

clearly to technical and non-technical stakeholders. Essential Skills & Experience Hands-on experience in ML, NLP, and GenAI (LLM/SLM). Proficiency in Python (Pandas, NumPy, Scikit-learn, PyTorch/TensorFlow). Experience with SQL/NoSQL databases, APIs, and data integration. Exposure to on-premise/open-source AI frameworks. Strong problem-solving and communication skills. Preferred Knowledge More ❯

clearly to technical and non-technical stakeholders. Essential Skills & Experience Hands-on experience in ML, NLP, and GenAI (LLM/SLM). Proficiency in Python (Pandas, NumPy, Scikit-learn, PyTorch/TensorFlow). Experience with SQL/NoSQL databases, APIs, and data integration. Exposure to on-premise/open-source AI frameworks. Strong problem-solving and communication skills. Preferred Knowledge More ❯

products. For this role, we're looking for skills across the following: Strong Python proficiency with hands-on experience in AI/ML frameworks including RAG, LangChain, TensorFlow, and PyTorch Practical experience with Generative AI and exposure to leading LLM platforms (Anthropic, Meta, Amazon , OpenAI) Proficiency with essential data science libraries including Pandas, NumPy, scikit-learn, Plotly/Matplotlib, and More ❯

ML models into products. Contribute to improving infrastructure, tooling, and best practices for ML development and deployment. Skills & Experience Essential: Strong programming skills in Python (and frameworks such as PyTorch, TensorFlow, or Scikit-learn). Proven experience in developing and deploying machine learning models in production. Solid understanding of data structures, algorithms, and software engineering principles. Experience with ML pipelines More ❯

ML models into products. Contribute to improving infrastructure, tooling, and best practices for ML development and deployment. Skills & Experience Essential: Strong programming skills in Python (and frameworks such as PyTorch, TensorFlow, or Scikit-learn). Proven experience in developing and deploying machine learning models in production. Solid understanding of data structures, algorithms, and software engineering principles. Experience with ML pipelines More ❯

ML models into products. Contribute to improving infrastructure, tooling, and best practices for ML development and deployment. Skills & Experience Essential: Strong programming skills in Python (and frameworks such as PyTorch, TensorFlow, or Scikit-learn). Proven experience in developing and deploying machine learning models in production. Solid understanding of data structures, algorithms, and software engineering principles. Experience with ML pipelines More ❯

Programming: Solid experience in Python and SQL. Experience with R is a nice-to-have. ML and AI: Practical experience using ML modeling libraries like Scikit-Learn, Keras, TensorFlow, PyTorch and similar Generative AI: Some hands-on experience with LLMs for prompt engineering or agents is preferred Cloud Expertise: Building, deploying and monitoring models on cloud like Azure, AWS or More ❯

Programming: Solid experience in Python and SQL. Experience with R is a nice-to-have. ML and AI: Practical experience using ML modeling libraries like Scikit-Learn, Keras, Tensorflow, PyTorch and similar Generative AI: Some hands-on experience with LLMs for prompt engineering or agents is preferred Cloud Expertise: Building, deploying and monitoring models on cloud like Azure, AWS or More ❯

and implementing solutions defined by project leads. Desirable Experience Strong Python expertise. Experience with GNU/Linux environments. Familiarity with key data science and ML frameworks (e.g., scikit-learn, PyTorch, TensorFlow, XGBoost, Hugging Face). Experience in natural language processing, tabular data analysis, or computer vision. SQL proficiency. Exposure to containerisation (Docker, Kubernetes) and cloud-native architectures. Experience with CI More ❯

for Active SC clearance(minimum 5 years UK residency required). Strong software engineering skills, with proficiency in Python. Experience across the ML lifecycle, including deploying models built in PyTorch, TensorFlow, or Scikit-learn. Hands-on cloud experience with AWS, Azure, or GCP. Knowledge of Docker and Kubernetes, with practical containerisation experience. Understanding of probability, statistics, and ML techniques. Strong More ❯

and implementing solutions defined by project leads. Desirable Experience Strong Python expertise. Experience with GNU/Linux environments. Familiarity with key data science and ML frameworks (e.g., scikit-learn, PyTorch, TensorFlow, XGBoost, Hugging Face). Experience in natural language processing, tabular data analysis, or computer vision. SQL proficiency. Exposure to containerisation (Docker, Kubernetes) and cloud-native architectures. Experience with CI More ❯

scripts, and building custom scenarios to prove a point. Highly Desired: Direct experience with our specific AI domain (e.g., experience with LangChain for an LLM company, or TensorFlow/PyTorch for a computer vision company). Understanding of MLOps principles and the end-to-end machine learning lifecycle. Programming/scripting experience (e.g., Python, SQL) to manipulate data and interact More ❯

scripts, and building custom scenarios to prove a point. Highly Desired: Direct experience with our specific AI domain (e.g., experience with LangChain for an LLM company, or TensorFlow/PyTorch for a computer vision company). Understanding of MLOps principles and the end-to-end machine learning lifecycle. Programming/scripting experience (e.g., Python, SQL) to manipulate data and interact More ❯

scripts, and building custom scenarios to prove a point. Highly Desired: Direct experience with our specific AI domain (e.g., experience with LangChain for an LLM company, or TensorFlow/PyTorch for a computer vision company). Understanding of MLOps principles and the end-to-end machine learning lifecycle. Programming/scripting experience (e.g., Python, SQL) to manipulate data and interact More ❯

environments. Proficiency in API development and integration (REST, gRPC, GraphQL preferred). Familiarity with Python , Java , or similar languages used in model deployment. Experience with ML frameworks (eg, TensorFlow, PyTorch, Scikit-learn) and model serving tools (eg, FastAPI, Flask, TorchServe, TensorFlow Serving). Understanding of cloud platforms (AWS, Azure, GCP) and containerization technologies (Docker, Kubernetes). Strong communication and collaboration More ❯

Key Responsibilities: Research and deploy LLM-based solutions (e.g., LangChain, Mastra.ai, Pydantic) for document processing, summarization, and clinical Q&A systems. Develop and optimize predictive models using scikit-learn, PyTorch, TensorFlow, and XGBoost. Design robust data pipelines using tools like Spark and Kafka for real-time and batch processing. Manage ML lifecycle with tools such as Databricks , MLflow , and cloud More ❯

experience in full-stack software development (React, FastAPI, Django, Node.js, etc.). Strong background in cheminformatics concepts and toolkits (RDKit, SMARTS/SMIRKS). Proficiency with machine learning frameworks (PyTorch, TensorFlow, scikit-learn). Experience deploying applications in cloud environments (AWS, GCP, or Azure). Knowledge of modern software practices (CI/CD, Git, testing, code review). Excellent communication More ❯

experience in full-stack software development (React, FastAPI, Django, Node.js, etc.). Strong background in cheminformatics concepts and toolkits (RDKit, SMARTS/SMIRKS). Proficiency with machine learning frameworks (PyTorch, TensorFlow, scikit-learn). Experience deploying applications in cloud environments (AWS, GCP, or Azure). Knowledge of modern software practices (CI/CD, Git, testing, code review). Excellent communication More ❯

experience in full-stack software development (React, FastAPI, Django, Node.js, etc.). Strong background in cheminformatics concepts and toolkits (RDKit, SMARTS/SMIRKS). Proficiency with machine learning frameworks (PyTorch, TensorFlow, scikit-learn). Experience deploying applications in cloud environments (AWS, GCP, or Azure). Knowledge of modern software practices (CI/CD, Git, testing, code review). Excellent communication More ❯

to junior engineers, championing best practice and technical standards. What We're Looking For Strong experience across the ML lifecycle, including deploying models built in frameworks such as TensorFlow, PyTorch or Scikit-learn. Solid software engineering skills, with strong Python programming experience. Hands-on knowledge of cloud platforms (AWS, Azure, or GCP), containers, Docker, and Kubernetes. Understanding of probability, statistics More ❯