26 to 50 of 256 TensorFlow Jobs in the UK excluding London

across the Civil Service. Key Skills and Experience • Strong programming skills in Python, R, or SQL. • Experience with machine learning frameworks (e.g., Scikit-learn, TensorFlow, PyTorch). • Proficiency in data manipulation and analysis (e.g., Pandas, NumPy, Spark). • Knowledge of data visualization tools (e.g., Power BI, Tableau, Matplotlib). More ❯

For Education & Experience – Strong academic background in Data Science, Machine Learning, AI, or a related field. Technical Skills – Proficiency in Python, SQL, ML frameworks (TensorFlow, PyTorch, scikit-learn), and at least one OOP language (Rust, C++, C#). AI & NLP Expertise – Hands-on experience with LLMs, NLP, and AI More ❯

programming skills in Python or R, with proficiency in data manipulation libraries (e.g., Pandas, NumPy). Experience with machine learning frameworks (e.g., Scikit-Learn, TensorFlow) and data visualization tools (e.g., Tableau, Matplotlib). Solid understanding of statistics, probability, and data-driven decision-making. Experience working with databases (SQL) and More ❯

in machine learning/NLP roles, with recent focus on LLMs and/or GenAI. Strong proficiency in Python, deep learning frameworks (PyTorch or TensorFlow), and GenAI libraries (LangChain, LlamaIndex, Transformers). Hands-on experience with vector search, embedding models, and retrieval pipelines. Familiarity with prompt engineering, prompt tuning More ❯

frameworks like Streamlit) for dashboard creation. Experience with Machine Learning model development and data science workflows (including frameworks such as scikit-learn, PyTorch, or TensorFlow). Experience in Quantitative Finance or strong interest in mathematical/financial modeling, derivatives pricing, or algorithmic trading. Familiarity with ETRM platforms (e.g., OpenLink More ❯

Able to explain complex ideas simply, and work well in cross-functional teams Tech You'll Work With ML & Data Science Python (primary language) TensorFlow, PyTorch, or Keras NumPy, pandas Data pipelines (Azure Data Factory, Airflow, etc.) Applied ML: NLP, CV, transformers, GANs, time series, etc. Engineering & Cloud Azure More ❯

Able to explain complex ideas simply, and work well in cross-functional teams Tech You'll Work With ML & Data Science Python (primary language) TensorFlow, PyTorch, or Keras NumPy, pandas Data pipelines (Azure Data Factory, Airflow, etc.) Applied ML: NLP, CV, transformers, GANs, time series, etc. Engineering & Cloud Azure More ❯

. Stay up-to-date with the latest research and advancements in AI, Image processing, and Computer Vision. Familiarity with deep learning frameworks (PyTorch, TensorFlow) including OpenCV. Strong communication and analytical skills. Ability to work in teams in a diverse, multi-stakeholder environment comprising of Business and Technology teams. More ❯

or related field research - Experience programming in Java, C++, Python or related language - 3+ years' experience with modeling languages and tools like PyTorch/TensorFlow, R, scikit-learn, numpy, scipy, etc - Solid ML background and familiar with standard NLU, NLG, and LLM techniques PREFERRED QUALIFICATIONS - PhD in Computer Sciences More ❯

foundation in both machine learning and software engineering. Experience deploying machine learning models in production environments. Proficiency in Python and relevant ML libraries (e.g., TensorFlow, PyTorch, scikit-learn). Familiarity with cloud platforms like GCP, AWS, or Azure. Experience with CI/CD pipelines for machine learning (e.g., Vertex More ❯

a plus. Hands-on experience with Google Cloud AI tools, such as Vision AI, Speech-to-Text, or AutoML. Proficiency in ML frameworks like TensorFlow, PyTorch, or Scikit-learn. Expertise in container orchestration for AI workloads using Google Kubernetes Engine (GKE) or Kubernetes. Background in software engineering, data science More ❯

and on-premises deployments. Required Qualifications: Strong experience in AI/ML development focusing on LLMs and biomedical NLP. Proficiency in deep learning frameworks (TensorFlow, PyTorch). Experience with MLOps tools and cloud environments (AWS, Azure, GCP). Expertise in model inference optimization techniques. Understanding of biomedical ontologies and More ❯

years of experience in machine learning engineering, with a strong focus on productionizing ML models and MLOps. Proficiency in Python and ML libraries (e.g., TensorFlow, PyTorch, Scikit-learn). Strong experience with cloud platforms (AWS, GCP, or Azure) and containerization (Docker, Kubernetes). Hands-on experience with CI/ More ❯

s degree in Data Science, Computer Science, Statistics, Applied Mathematics, or a related field You have strong proficiency in Python, leveraging libraries like Prophet, TensorFlow, Keras, and PyTorch for LSTM, along with expertise in SQL and machine learning frameworks You have hands-on experience with leading time series forecasting More ❯

coursework in machine learning, deep learning, or AI techniques (e.g., supervised learning, neural networks, NLP). Proficiency in Python and libraries like Scikit-learn, TensorFlow, PyTorch, or Hugging Face Transformers. Familiarity with data preprocessing, model evaluation, and deploying models in real-world environments. A passion for AI innovation and More ❯

Implementing MLOps best practices for seamless model deployment, monitoring, and iteration. What We’re Looking For: 🔹 Strong Python skills – You know your way around TensorFlow, PyTorch, or Hugging Face. 🔹 Experience with LLMs, NLP, or recommendation algorithms . 🔹 Familiarity with MLOps, APIs, and scalable cloud solutions . 🔹 Passion for AI More ❯

and deploying machine learning models and algorithms in real-world applications. - Strong proficiency in Python programming and popular machine learning libraries/frameworks (eg, TensorFlow, PyTorch, scikit-learn). - Deep understanding of machine learning concepts and techniques, including supervised/unsupervised learning, deep learning, reinforcement learning, etc. - Strong communication More ❯

strong emphasis on threat detection. Solid experience in machine learning and data science, proficient in both supervised and unsupervised algorithms and frameworks such as TensorFlow, PyTorch, or Scikit-learn. Experience working with large, real-world datasets that require pre-processing, data visualization, and a great dose of analytical skills. More ❯

and high availability. Very strong technical background leading application development - with experience in some or all of the following technologies: Python, Java, Spring Boot, TensorFlow, PyTorch, Apache Spark, Kafka, Jenkins, Git/Bitbucket, Terraform, Docker, ECS/EKS, IntelliJ, JIRA, Confluence, React/Typescript, Selenium, Redux, Junit, Cucumber/ More ❯

vision challenges Knowledgeable about key architectures like Vision Transformers, DeepLabv3, and SegFormer Proficient in Python and ML tools, including Scikit-Learn, NumPy, Pandas, PyTorch, TensorFlow, or Keras Capable of applying machine learning to solve real-world problems Please apply via the link for immediate consideration More ❯

AI solutions into business workflows. Required Qualifications & Skills Strong experience in AI, NLP, and machine learning algorithms. Proficiency in Python and frameworks such as TensorFlow, PyTorch, or Hugging Face. Hands-on experience with generative AI and LLM fine-tuning . Experience deploying AI applications on Azure (e.g., Azure ML More ❯

building AI/ML software. Strong expertise in machine learning and neural network algorithms. Proficient in programming languages like Python, and libraries such as TensorFlow, PyTorch, NumPy and LangChain Experience with server deployment, cloud computing environments, and API development. Good understanding of software engineering best practices. Excellent problem-solving More ❯

ML development. Strong understanding of AI/ML algorithms and techniques, including LLMs, GenAI, and automated AI systems. Experience with machine learning frameworks (e.g., TensorFlow, PyTorch). Skills & Competencies: Must Have: Proficiency in Python, R, or other relevant programming languages. Proficiency in working with large datasets, data wrangling, and More ❯

architectures. Knowledge of data pipelines, analytics tooling, or large-scale data processing. Interest in cloud-native and serverless architectures. Familiarity with tools such as TensorFlow, PyTorch, or LangChain is a plus. More ❯

Looking For: 2+ years in AI/ML engineering or backend software roles with ML components. Proficiency in Python and frameworks like PyTorch/TensorFlow, Scikit-learn. Experience deploying models with Docker, Kubernetes, or serverless architectures. Solid grasp of MLOps workflows, versioning, and cloud automation. Strong foundations in algorithms More ❯