26 to 50 of 150 PyTorch Jobs in England

services using Microsoft and .NET . 4+ years in a Data Scientist or AI/ML Engineer role. Proficiency in Python , including libraries like pandas , scikit-learn , TensorFlow , and PyTorch . Deep understanding of ML algorithms : regression, classification, clustering, and deep learning. Hands-on experience with Large Language Models (LLMs) and techniques such as Retrieval-Augmented Generation (RAG) , agent orchestration More ❯

programming background; must be able to quickly become fluent in Python . Proficiency with key data science libraries (NumPy, Pandas, Scikit-Learn) and experience with deep learning frameworks (TensorFlow, PyTorch, or Caffe). Strong mathematical and statistical skills. Broad knowledge of core data science techniques, such as: Supervised/unsupervised machine learning Cross-validation and Bayesian inference Time-series analysis More ❯

to join our growing teams in Newcastle or Erskine. Key Responsibilities Strong proficiency in Python and ML libraries such as: pandas, NumPy, scikit-learn XGBoost, LightGBM, CatBoost TensorFlow, Keras, PyTorch Experience with model deployment and serving tools: ONNX, TensorRT, TensorFlow Serving, TorchServe Familiarity with ML lifecycle tools: MLflow, Kubeflow, Azure ML Pipelines Experience working with distributed data processing using PySpark. More ❯

managing ML in production. What we're looking for Active SC Clearance Strong software engineering background with proficiency in Python. Experience deploying ML models built with frameworks such as PyTorch, TensorFlow, or Scikit-learn. Knowledge of probability, statistics, and common ML techniques. Hands-on experience with at least one major cloud platform (AWS, Azure, or GCP). Proficiency with containers More ❯

solutions independently. Ideal Experience 5+ years in applied Machine Learning, with significant hands-on NLP project experience. Deep understanding of transformer models and LLM fine-tuning. Proficient in Python, PyTorch or TensorFlow, and scikit-learn. Practical experience deploying ML models in production environments (cloud-native or on-prem). Familiar with data versioning, MLflow, and monitoring frameworks (e.g. Weights & Biases More ❯

proficient in data wrangling (SQL, pandas, NumPy) and scripting. You'll be skilled in supervised and unsupervised learning, model evaluation, and feature engineering. Knowledgeable in Deep Learning frameworks like PyTorch, with experience in various neural networks and NLP models. Exposure to generative and multi-modal models is a plus. A practitioner of MLOps, experienced in model serving, orchestration (Kubernetes), and More ❯

intelligence and its application to drug discovery Understanding of ligand- and structure-based drug design. Experience with machine learning and major machine learning frameworks such as scikit-learn or PyTorch Proficiency in a low-level programming language such as C/C++ or Rust. Knowledge of advanced data analysis techniques such as multi-parameter optimization Open source contributions or publications More ❯

current with emerging research, tools, and trends in Artificial Intelligence. ---------------------------------------- Skills, Knowledge, and Experience Strong proficiency in Python and experience writing scalable, production-ready code. Hands-on experience with PyTorch, Transformer architectures, and Large Language Models (LLMs). Demonstrated success delivering Computer Vision and/or NLP/LLM projects into production. Solid understanding of model deployment, pipelines, and software More ❯

learning architectures. Strong understanding of two-tower neural networks, embedding techniques, and ranking models. Proficiency in Python with familiarity to ML libraries e.g. pandas, numpy, scipy, scikit-learn, tensorflow, pytorch) Familiarity with cloud platforms (GCP, AWS, Azure) and tools like Dataiku. Experience with ML Ops, including model deployment, monitoring, and retraining pipelines. Ability to work cross-functionally with marketing, CRM More ❯

LLM and graph analytics and hands-on experience and solid understanding of machine learning and deep learning methods Extensive experience with machine learning and deep learning toolkits (e.g.: TensorFlow, PyTorch, NumPy, Scikit-Learn, Pandas) Ability to design experiments and training frameworks, and to outline and evaluate intrinsic and extrinsic metrics for model performance aligned with business goals Preferred Qualifications, Capabilities More ❯

Data Science with reasonable industry experience, or an MS with significant industry or research experience in the field • Extensive experience with machine learning and deep learning toolkits (e.g.: TensorFlow, PyTorch, NumPy, Scikit-Learn, Pandas) • Ability to design experiments and training frameworks, and to outline and evaluate intrinsic and extrinsic metrics for model performance aligned with business goals • Experience with big More ❯

R&D challenges that directly impact customers. Our Technology Stack: Python Agentic tools (Autogen, Semantic Kernel, LangChain) SQL MongoDB Third-party LLM APIs LiteLLM MLflow Google Cloud Platform Docker PyTorch Hugging Face Transformers SPARQL Kubernetes WHAT YOU WILL BE DOING AT BEAMERY Strategic AI Leadership Define and implement the company's AI and data science strategy, ensuring alignment with long More ❯

sequential (e.g. sensor time-series) data and decision-making post PhD Experience in software development for proof of concept in Python Experience with machine and deep learning frameworks: TensorFlow, PyTorch, scikit-learn, etc. Of particular interest are candidates with experience in one or more of the following domains: RF communications and CEMA Electronic or Electromagnetic Warfare (EW) Tracking and sensor More ❯

in Artificial Intelligence. Skills, Knowledge, and Experience Technical proficiency You write production-grade, scalable Python code, ensuring that your models are robust, maintainable, and optimised for performance. Comfortable with PyTorch Knowledge of Transformer-based models Knowledge of Large Language Models (LLMs) Proven experience of having delivered successful machine learning projects into production Strong understanding of software development fundamentals, in particular More ❯

BASIC QUALIFICATIONS - 5+ years of hands-on experience optimizing AI infrastructure, with deep expertise in inference acceleration frameworks (e.g., vLLM, SGLang, TensorRT, etc.), model training and serving systems across PyTorch and TensorFlow ecosystems; - Advanced proficiency in Nvidia GPU performance optimization techniques, including memory management, kernel fusion, and quantization strategies for large-scale deep learning workloads; - Strong foundation in parallel computing More ❯

Jazz Data Science and across Jazz Research and Development. Required Knowledge, Skills and Abilities Strong programming skills in Python, R, or similar languages, with experience in modern ML frameworks (PyTorch, TensorFlow). Demonstrated experience with generative AI technologies, including LLM architectures and frameworks. Knowledge/experience with digital healthcare tools design and development Experience with natural language processing and generative More ❯

Jazz Data Science and across Jazz Research and Development. Required Knowledge, Skills and Abilities Strong programming skills in Python, R, or similar languages, with experience in modern ML frameworks (PyTorch, TensorFlow). Demonstrated experience with generative AI technologies, including LLM architectures and frameworks. Knowledge/experience with digital healthcare tools design and development Experience with natural language processing and generative More ❯

to AI/ML and serverless computing. Proficiency in JavaScript, TypeScript, Node.js, React.js, and Express.js for building full-stack applications. Experience with AI/ML frameworks such as TensorFlow, PyTorch, OpenAI API, or LangChain. Knowledge of microservices architecture, containerization (Docker, Kubernetes), and event-driven patterns. Strong understanding of API design, including REST, GraphQL, and WebSockets. Familiarity with DevOps practices, CI More ❯

ML engineering, with a strong focus on NLP and LLMs. Proven hands-on knowledge with: LangChain, AutoGen, LangGraph and RAG Strong proficiency in Python and experience with frameworks like PyTorch or TensorFlow. Experience working with vector databases (e.g., FAISS, Weaviate, Pinecone). Familiarity with HR systems and data (Workday, SAP SuccessFactors, etc.) is a plus. Excellent communication skills and ability More ❯

ML engineering, with a strong focus on NLP and LLMs. Proven hands-on knowledge with: LangChain, AutoGen, LangGraph and RAG Strong proficiency in Python and experience with frameworks like PyTorch or TensorFlow. Experience working with vector databases (e.g., FAISS, Weaviate, Pinecone). Familiarity with HR systems and data (Workday, SAP SuccessFactors, etc.) is a plus. Excellent communication skills and ability More ❯

deep learning algorithms including the latest multimodal foundation models and generative AI frameworks' exploration, development, and implementation. Extensive experience with common machine learning Python frameworks such as TensorFlow and PyTorch; and Python libraries such as pandas, and computer vision libraries such as OpenCV. Experience in ONNX and TensorRT. Very comfortable working in Linux environment. Familiarity with software development tools and More ❯

translating technical methods to non-technical stakeholders Strong programming experience in python (R, Python, C++ optional) and the relevant analytics libraries (e.g., pandas, numpy, matplotlib, scikit-learn, statsmodels, pymc, pytorch/tf/keras, langchain) Experience with version control (GitHub) ML experience with causality, Bayesian statistics & optimization, survival analysis, design of experiments, longitudinal analysis, surrogate models, transformers, Knowledge Graphs, Agents More ❯

modelling and deep learning techniques, with hands-on experience in probabilistic methods and predictive modelling. Expertise in python, along with proficiency in libraries like NumPy, SciPy, Pandas, TensorFlow and PyTorch, is essential, with the ability to deploy scalable, production-ready models and data pipelines. With at least 1 year industry experience (post Masters or PhD) in a commercial, non-research More ❯

and learn on the job. You would have experience with some of the following technologies and areas: Python and ML/NLP frameworks such as scikit-learn, TensorFlow, or PyTorch Large/Small Language Models (LLMs/SLMs) and libraries like Hugging Face Transformers Prompt engineering for tasks like summarization, Q&A, or information extraction Fine-tuning transformer-based models More ❯

governance standards. Contribute to the development of AI best practices and frameworks. Essential Skills Active SC Clearance (must be current) Strong experience in AI/ML engineering (Python, TensorFlow, PyTorch, etc.) Experience with cloud platforms (AWS, Azure, or GCP) Solid understanding of data pipelines, APIs, and MLOps Excellent problem-solving and communication skills More ❯