76 to 100 of 333 PyTorch Jobs in England

knowledge, and promotes best practices. Excellent communicator, able to work cross-functionally and tailor messages to different audiences. Hands-on expertise in Python, SQL, ML frameworks (e.g. XGBoost, TensorFlow, PyTorch), and cloud tools (GCP, BigQuery, Vertex AI). Familiar with generative AI tools and frameworks (e.g. OpenAI, HuggingFace, LangChain). Deeply curious, commercially minded, and impact-driven with strong critical More ❯

in a collaborative environment, this is an excellent opportunity to take the next step in your career. Essential Solid programming knowledge with Python Experience using Pandas, NumPy, Matplotlib, and PyTorch Strong understanding of SQL for querying and data manipulation Familiarity with CI/CD workflows and Git version control Detail-oriented and proactive problem solver Enthusiastic about using data to More ❯

an active role in open source communities. Requirements Excellent programming abilities with experience in relevant languages (Python, Rust, C++ and/or Go) Experience with relevant libraries/tools (PyTorch, Tensorflow, Neo4j) and/or AI accelerators (GPU, TPU) is a plus Deep understanding of open source development processes (RFCs/proposals, GitHub pull requests) with demonstrable contributions to open More ❯

solutions. Strong engineering fundamentals, including DevOps, CI/CD, and secure ML/AI pipelines (DevSecOps). Highly proficient in Python, SQL, and key AI/ML frameworks (e.g., PyTorch, TensorFlow). Ability to mitigate model hallucination, optimise performance, and lead governance around AI risk and ethical deployment. Ready to Transform the Future? This a career-defining opportunity working within More ❯

solutions. Strong engineering fundamentals, including DevOps, CI/CD, and secure ML/AI pipelines (DevSecOps). Highly proficient in Python, SQL, and key AI/ML frameworks (e.g., PyTorch, TensorFlow). Ability to mitigate model hallucination, optimise performance, and lead governance around AI risk and ethical deployment. Ready to Transform the Future? This a career-defining opportunity working within More ❯

solutions. Strong engineering fundamentals, including DevOps, CI/CD, and secure ML/AI pipelines (DevSecOps). Highly proficient in Python, SQL, and key AI/ML frameworks (e.g., PyTorch, TensorFlow). Ability to mitigate model hallucination, optimise performance, and lead governance around AI risk and ethical deployment. Ready to Transform the Future? This a career-defining opportunity working within More ❯

solutions. Strong engineering fundamentals, including DevOps, CI/CD, and secure ML/AI pipelines (DevSecOps). Highly proficient in Python, SQL, and key AI/ML frameworks (e.g., PyTorch, TensorFlow). Ability to mitigate model hallucination, optimise performance, and lead governance around AI risk and ethical deployment. Ready to Transform the Future? This a career-defining opportunity working within 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 ❯

and modern tooling (gRPC, Alembic, Pytest, etc.). Requirements: 13 years of experience in ML or AI Proficiency in Python, SQL, cloud platforms (Azure), and modern ML frameworks (TensorFlow, PyTorch). Familiarity with generative AI, deep learning, and the full development lifecycle. A proactive mindset and strong interest in innovative technologies. Why Join? Be part of a greenfield AI initiative More ❯

multi-objective optimization using machine learning and/or deep learning methods Experienced with common python toolkits for scientific computing (e.g., numpy, pandas, scipy), machine learning (e.g., scikit-learn, pytorch), and cheminformatics/bioinformatics (e.g., rdkit, openeye, biotite, biopython) Familiarity running simulations and training models on high-performance computing (GPU) environments for corporate R&D, innovation labs, or academic research More ❯

Machine Learning engines (AWS, Azure, Google, etc.) Experiencewith large scale data processing tools (Spark, Hadoop, etc.) Abilityto query and program databases (SQL, No SQL) Experiencewith distributed ML frameworks (TensorFlow, PyTorch, etc.) Familiaritywith collaborative software tools (Git, Jira, etc.) Experiencewith user interface libraries/applications (Shiny, Django, etc.) Experiencein developing ML or statistical models in the field of pricing (e.g. priceelasticity More ❯

deployment of ML models into production environments. Expertisein Python and relevant ML libraries Experience with various ML algorithms (e.g. supervised, unsupervised, reinforcement learning) and deep learning frameworks (e.g. TensorFlow,PyTorch). Experience developing generative AI applications and deploying them into production. Experience working with cloud platforms, ideally Google Cloud Platform (GCP) andBigQuery. Proficiencyin working with and querying global scale datasets. More ❯

deployment of ML models into production environments. Expertisein Python and relevant ML libraries Experience with various ML algorithms (e.g. supervised, unsupervised, reinforcement learning) and deep learning frameworks (e.g. TensorFlow,PyTorch). Experience developing generative AI applications and deploying them into production. Experience working with cloud platforms, ideally Google Cloud Platform (GCP) andBigQuery. Proficiencyin working with and querying global scale datasets. More ❯

applying deep learning and generative AI techniques, including implementing custom architectures, pretraining/fine-tuning generative models, building agentic workflows, and deploying solutions with real-world constraints. Familiarity with PyTorch, TensorFlow, JAX or similar frameworks Preferred Qualifications Experience in building AI agents (based on RL, LLMs, etc.) Experience in building multi-agent simulation Background in Large Language Models/NLP More ❯

in AI. Candidate Profile Essential skills: Bachelors, Masters, PhD, or equivalent experience in Machine Learning, Computer Science, Maths, Data Science, or related fields. Proficiency in deep learning frameworks like PyTorch or JAX. Strong Python software development skills (knowledge of C++ or other languages is a plus). Familiarity with deep learning fundamentals such as models, optimisation, evaluation, and scaling. Experience More ❯

CD pipelines (GitLab), and containerization (Docker). Strong Python programming skills: Strong programming skills in Python, including its ecosystem for AI/ML, with experience using libraries such as PyTorch, Hugging Face Transformers, scikit-learn, and TensorFlow to build and implement AI-driven solutions. Product mindset: Ability to think from the user's perspective and design solutions that align with More ❯

CD pipelines (GitLab), and containerization (Docker). Strong Python programming skills: Strong programming skills in Python, including its ecosystem for AI/ML, with experience using libraries such as PyTorch, Hugging Face Transformers, scikit-learn, and TensorFlow to build and implement AI-driven solutions. Product mindset: Ability to think from the user's perspective and design solutions that align with More ❯

CD pipelines (GitLab), and containerization (Docker). Strong Python programming skills: Strong programming skills in Python, including its ecosystem for AI/ML, with experience using libraries such as PyTorch, Hugging Face Transformers, scikit-learn, and TensorFlow to build and implement AI-driven solutions. Product mindset: Ability to think from the user's perspective and design solutions that align with More ❯

CD pipelines (GitLab), and containerization (Docker). Strong Python programming skills: Strong programming skills in Python, including its ecosystem for AI/ML, with experience using libraries such as PyTorch, Hugging Face Transformers, scikit-learn, and TensorFlow to build and implement AI-driven solutions. Product mindset: Ability to think from the user's perspective and design solutions that align with More ❯

Working with Data Scientists to deploy trained machine learning models into production environments Working with a range of models developed using common frameworks such as Scikit-learn, TensorFlow, or PyTorch Experience with software engineering best practices and developing applications in Python. Technical experience of cloud architecture, security, deployment, and open-source tools ideally with one of the 3 major cloud More ❯

Working with Data Scientists to deploy trained machine learning models into production environments Working with a range of models developed using common frameworks such as Scikit-learn, TensorFlow, or PyTorch Experience with software engineering best practices and developing applications in Python. Technical experience of cloud architecture, security, deployment, and open-source tools ideally with one of the 3 major cloud More ❯

production-grade code and a good understanding of data engineering & MLOps Solid understanding of machine learning concepts, familiarity working with common frameworks such as sci-kit-learn, TensorFlow, or PyTorch Collaborative and humble team player with an ability to work with cross-functional teams, including technical and non-technical stakeholders Passion for learning new skills and staying up-to-date More ❯

how of designing and implemention synchronous, asynchronous and batch data processing operations Expert level programming skills in Python, along with experience in using relevant tools and frameworks such as PyTorch, FastAPI and Huggingface; strong programming skills in Java are a plus Expert level know-how of ML Ops systems, data pipeline design and implementation, and working with ML platforms (preferably More ❯

Engineering, or related technical field 2+ years of experience in AI/ML development with a focus on practical applications Strong proficiency in Python and relevant AI libraries (TensorFlow, PyTorch, Hugging Face) Hands-on experience with workflow automation platforms like N8N, AirTable, and proven track-record. Experience with AI agent development and testing methodologies using Google ADK, LangGraph, Llamaindex Understanding More ❯

Scientific publications in top-tier AI and neuroscience conferences (NeurIPS, ICLR, ICML, AAAI, CVPR, Cosyne, SFN, CNN ecc) or peer reviewed journals Familiarity with deep learning libraries such as Pytorch, Huggingface, Transformers, Accelerator and Diffuser. Hands-on experience in training and fine-tuning generative models like diffusion models or large language models such as GPTs and LLAMAs. Experience with data More ❯