1 to 25 of 149 PyTorch Jobs in the UK

5+ years) as a Machine Learning Engineer , Data Scientist , or similar role. Strong programming skills in Python (experience with libraries such as TensorFlow, PyTorch, scikit-learn, pandas, NumPy). Solid understanding of machine learning algorithms , statistical modelling , and deep learning architectures . Hands-on experience with MLOps tools and frameworks ...

organisation. Required Experience & Skills AI/Technical Strong experience building and deploying machine learning and AI solutions in production. Hands‐on experience with: Python (PyTorch, TensorFlow, scikit‐learn) Data engineering tools (SQL, Spark, Airflow or similar) LLMs, NLP, and document intelligence (e.g. RAG, embeddings) Experience with cloud platforms (AWS, Azure ...

work in the UK (we are unable to offer visa sponsorship for this role) Desirable (Not Essential): Familiarity with deep learning frameworks (e.g. TensorFlow, PyTorch) Exposure to cloud platforms (AWS, GCP, or Azure) Experience with experimental design, research methods, or academic publishing Understanding of MLOps, version control (Git), or containerisation ...

GenAI Ecosystem Lead the design and deployment of scalable AI solutions across Python, .NET, and cloud-native platforms Drive adoption of advanced frameworks (PyTorch, TensorFlow, Hugging Face, LangChain) Oversee integration of LLMs (OpenAI, Anthropic, Gemini, Mistral) via enterprise platforms (Azure OpenAI, Vertex AI) Implement RAG architectures and manage vector databases ...

models, or LLM-based analytics. Strong proficiency in Python (preferred) and/or JavaScript/TypeScript. Hands-on experience with AI frameworks (e.g. TensorFlow, PyTorch and/or LangChain) and LLM APIs (e.g. Azure OpenAI, OpenAI API, Anthropic and/or AWS Bedrock). Experience with Microsoft Bot Framework, Dialogflow ...

Stay up to date with the latest advancements in machine learning and AI technologies Required Skills & Experience Strong programming skills in Python (e.g., TensorFlow, PyTorch, Scikit-learn) Experience deploying ML models using cloud platforms (AWS, Azure, or GCP) Solid understanding of machine learning algorithms, data structures, and software engineering principles ...

into domain-specific use cases Retrieval-Augmented Generation (RAG) fundamentals and context engineering Hands-on or strong exposure to Python and common AI libraries (PyTorch, TensorFlow). Familiarity with: LLMs (OpenAI, Anthropic, Hugging Face, LLaMA models) Vector databases (Pinecone, Weaviate, FAISS , Qudrant) Agentic AI frameworks (exposure to LangGraph, AutoGen, CrewAI ...

through metrics like Character Error Rate (CER) and Word Error Rate (WER) is also crucial. Strong proficiency in Python and ML frameworks (e.g., TensorFlow, PyTorch). Understanding of ML architectures, hyperparameter tuning, and performance optimisation. Experience with MLOps tools and CI/CD pipelines. Familiarity with data engineering concepts ...

data workflows for maximum scalability and cost-efficiency. Insurance Domain experience is added advantage. Your Technical Toolkit AI/ML: Expert proficiency in Python , PyTorch/TensorFlow, and GenAI frameworks like LangChain, LlamaIndex, or CrewAI . Data Architecture: Hands-on experience with Vector Databases (e.g., Pinecone, Milvus, Weaviate ...

data workflows for maximum scalability and cost-efficiency. Insurance Domain experience is added advantage. Your Technical Toolkit AI/ML: Expert proficiency in Python , PyTorch/TensorFlow, and GenAI frameworks like LangChain, LlamaIndex, or CrewAI . Data Architecture: Hands-on experience with Vector Databases (e.g., Pinecone, Milvus, Weaviate ...

consulting incl software development with a strong track record of delivering business value Proficiency in Python and ML/DL frameworks (e.g., scikit-learn, PyTorch, TensorFlow) Experience with AI/ML tools (e.g., Jupyter, MLflow, Vertex AI, Azure ML, Amazon SageMaker Experience of creating delivery client-facing proof of concepts ...

Significant experience building, training and deploying machine learning models Strong Python skills with experience using NumPy, Pandas, SciPy and modern ML frameworks such as PyTorch or TensorFlow Experience working with large-scale unstructured data Experience building and deploying production-ready NLP systems Familiarity with API integrations and data acquisition pipelines ...

BI. Published work, patents or conference presentations related to AI or data science in finance. Technical Skills Programming: Python (pandas, scikit‐learn, TensorFlow/PyTorch), R, SQL, Jupyter notebooks and version control (Git). Machine Learning: regression, classification, clustering, tree‐based models, neural networks, MLOps practices and model deployment. Data ...

drift with W&B or MLflow and ensure Responsible AI (bias detection, red teaming). Technical Profile Languages: Python (Expert), SQL, and Bash. Frameworks: PyTorch, Transformers, LlamaIndex, and LangChain. Infrastructure: Kubernetes, Helm, and Cloud (AWS/GCP/Azure) Key Skills: RAG optimization, Multi-agent orchestration ...

with emerging machine learning technologies and best practices Skills and Experience • Strong programming skills in Python • Experience with machine learning frameworks such as TensorFlow, PyTorch, or Scikit-learn • Experience working with SQL and large datasets • Familiarity with data pipelines, feature engineering, and model optimisation • Understanding of MLOps practices, model deployment ...

. Published research, patents, or conference presentations in AI or data science related to finance. Technical Skills Programming: Python (pandas, scikit‐learn, TensorFlow/PyTorch), R, SQL, notebooks, Git. Machine Learning: regression, classification, clustering, tree‐based models, neural networks; MLOps, model deployment, automated testing. Data Platforms: relational databases, NoSQL, time ...

databases Strong analytical thinking and problem-solving skills Ability to work remotely in UK time zones Preferred Qualifications Exposure to deep learning frameworks (TensorFlow, PyTorch) Experience with cloud platforms (AWS, GCP, or Azure) Knowledge of real-world data science applications (e.g., recommendation systems, NLP, forecasting) Prior internship or project experience ...

technologies and Semantic Search techniques & tools. Experience in writing robust and efficient code in Python. Experience in using tools relevant to deep learning like PyTorch, TensorFlow, LangChain. Experience in designing & implementing key MLOps capabilities & frameworks in delivering robust train, test, monitor and improve lifecycles for AI/ML model deployments. ...

technologies and Semantic Search techniques & tools. Experience in writing robust and efficient code in Python. Experience in using tools relevant to deep learning like PyTorch, TensorFlow, LangChain. Experience in designing & implementing key MLOps capabilities & frameworks in delivering robust train, test, monitor and improve lifecycles for AI/ML model deployments. ...

Statistics, or a related field Strong expertise in Large Language Models and advanced fine-tuning techniques Hands-on experience with ML frameworks such as PyTorch, TensorFlow, or scikit-learn Experience with Generative AI tools like LangChain, Weaviate, LangGraph, or LlamaIndex Advanced programming skills in Python Competitive programming or data science ...

core data science libraries: Pandas, NumPy, and SciPy . Machine Learning: Deep, practical experience with popular ML frameworks and libraries: scikit-learn, TensorFlow, or PyTorch . Statistics & Math: Strong foundation in statistical modeling , probability, hypothesis testing, regression analysis, and multivariate calculus/linear algebra for understanding model mechanics. Databases & Querying ...

learning solutions for personalizing recommendations. Hands-on experience building training frameworks and/or serving large-scale models using tools such as Tensorflow or PyTorch is a plus. You stay up-to-date with the state-of-the-art open source infrastructure solutions applicable to designing and improving large scale ...

building, deploying, and maintaining ML systems in production, beyond research prototypes. Strong Python skills and hands-on experience with modern ML frameworks such as PyTorch or TensorFlow and MLOps frameworks such as ClearML, Flyte, and MLFlow. Demonstrated experience across the full ML lifecycle: data preparation, training, evaluation, deployment, monitoring ...

selecting appropriate modeling approaches for each. Strong proficiency in Python and SQL, with hands‐on experience using major ML libraries/frameworks (e.g., PyTorch, TensorFlow, scikit‐learn) for model development and evaluation. Deep understanding of machine learning algorithms, model evaluation techniques (e.g., AUC, lift, calibration, stability), and data pipeline development ...

Skills & Experience Strong experience with Python and/or Node.js in production environments Hands-on expertise with LLM frameworks: LangChain, LlamaIndex Deep experience with PyTorch for model training and fine-tuning Proven experience with vector databases: Pinecone. Azure Vector Store Experience building voice-enabled AI systems using: Whisper, ElevenLabs, Azure ...