1 to 25 of 263 TensorFlow Jobs in the UK excluding London

algorithms and NLP techniques, with hands-on experience in either academia or industry. Proficiency in Python and experience with ML/NLP libraries like TensorFlow, PyTorch, scikit-learn, or Hugging Face. Experience working with cloud platforms such as AWS, GCP, or Azure. Familiarity with advanced NLP methods, including Prompt More ❯

how to fine-tune those models eg. XGBoost, Deep Neural Networks, Transformers, Markov chains, etc. Experience using specialized machine learning libraries e.g. Fastai, Keras, Tensorflow, pytorch, sci-kit learn, huggingface, etc. Must demonstrate the capacity of reading, understanding and implementing new techniques in the field of machine learning as More ❯

techniques and how to fine-tune those models e.g. XGBoost, Deep Neural Networks, Transformers, etc. Experience using specialized machine learning libraries e.g. Fastai, Keras, Tensorflow, pytorch, sci-kit learn, etc. Must demonstrate the capacity of reading, understanding and implementing new techniques in the field of machine learning as they More ❯

related field. Proficiency in programming languages such as Python, R, or Java. Strong understanding of mathematics and statistics. Experience with machine learning frameworks like TensorFlow, Keras, or PyTorch. Knowledge of data analysis and visualization tools (e.g., Pandas, NumPy, Matplotlib). Familiarity with big data technologies (e.g., Hadoop, Spark). More ❯

cloud platforms like Amazon Web Services (AWS), Google Cloud Platform (GCP), and Microsoft Azure. Technical Skills – Good to have: • Expertise in any one framework (TensorFlow, Pytorch, Keras) • Experience in a statistical programming language (e.g. R or Python) and applied machine learning and AI techniques (i.e computer vision, deep learning More ❯

and developing custom solutions using large language models (LLMs) for business use cases. Proficient in Python-based AI/ML development using frameworks like TensorFlow, PyTorch, and Scikit-learn. LLM Orchestration and Development Expertise in building LLM-powered applications using frameworks such as LangChain and LangGraph, including prompt engineering More ❯

computational linguistics are highly desirable, either from a research academic or commercial perspective. Proficiency in Python and ML libraries such as Hugging Face, PyTorch, TensorFlow, and Scikit-learn. Experience deploying AI solutions into production environments using AWS/GCP/Azure. Hands-on with MLOps, CI/CD for More ❯

in computer science, Software Engineering, or a related field. Proficiency in programming languages (e.g., Python, C#, C++). Experience with deep learning frameworks (e.g., TensorFlow, PyTorch). Knowledge of cloud platforms (e.g., Azure). Familiarity with containerization is a plus (e.g., Docker, Kubernetes). Knowledge of big data technologies More ❯

MLOps, DevOps, or ML Engineering roles Proven expertise deploying and scaling Generative AI models (GPT, Stable Diffusion, BERT) Proficiency with Python and ML frameworks (TensorFlow, PyTorch, Hugging Face) Strong cloud platform experience (AWS, GCP, Azure) and managed AI/ML services Practical experience with Docker, Kubernetes, and container orchestration More ❯

S3, Lambda, SageMaker, ECS) and cloud infrastructure management Programming and ML Frameworks: Proficiency in Python and experience with ML frameworks such as scikit-learn, TensorFlow, or PyTorch CI/CD Experience: Experience with CI/CD tools and practices (e.g., GitHub Actions, Jenkins) and the ability to design and More ❯

for you if: Python for API and Model development (Machine learning frameworks and tooling e.g. Sklearn) and (Deep learning frameworks such as Pytorch and Tensorflow). Understanding of machine learning techniques. Experience with data manipulation libraries (e.g. Pandas, Spark, SQL). Git for version control. Cloud experience (we use More ❯

for you if: Python for API and Model development (Machine learning frameworks and tooling e.g. Sklearn) and (Deep learning frameworks such as Pytorch and Tensorflow). Understanding of machine learning techniques. Experience with data manipulation libraries (e.g. Pandas, Spark, SQL). Git for version control. Cloud experience (we use More ❯

for you if: Python for API and Model development (Machine learning frameworks and tooling e.g. Sklearn) and (Deep learning frameworks such as Pytorch and Tensorflow). Understanding of machine learning techniques. Experience with data manipulation libraries (e.g. Pandas, Spark, SQL). Git for version control. Cloud experience (we use More ❯

Skills required: Programming: Proficiency in Python (preferred) and/or other relevant languages (e.g., R, Java, C++). Machine Learning & AI Frameworks: Experience with TensorFlow, PyTorch, Scikit-learn, or similar libraries. Data Manipulation & Analysis: Strong skills in Pandas, NumPy, and SQL for handling and analysing large datasets. Cloud Computing More ❯

performance. Requirements: Bachelor’s, Master’s, or PhD in Computer Science, Data Science, Bioinformatics, or related field. Proficiency in Python and ML frameworks (e.g., TensorFlow, PyTorch). Experience with bioinformatics tools (e.g., Biopython, RDKit). Strong knowledge of statistical models, deep learning, and data preprocessing. Familiarity with cloud platforms More ❯

ML workloads. Strong proficiency with Docker, Kubernetes, and infrastructure automation (Terraform, CloudFormation). Solid programming skills in Python and familiarity with ML frameworks like TensorFlow, PyTorch . Experience designing CI/CD pipelines for ML workflows and deployment automation. Exposure to LLM Ops , including managing fine-tuning and deployment More ❯

computational linguistics are highly desirable, either from a research academic or commercial perspective. Proficiency in Python and ML libraries such as Hugging Face, PyTorch, TensorFlow, and Scikit-learn. Experience deploying AI solutions into production environments using AWS/GCP/Azure. Hands-on with MLOps, CI/CD for More ❯

years of hands-on experience in AI and machine learning. Technical Expertise: Strong proficiency in Python. Expertise in machine learning frameworks such as TensorFlow, PyTorch, Keras, or similar. Machine Learning: Solid understanding of supervised and unsupervised learning, deep learning (CNNs, RNNs, GANs), and reinforcement learning. Data Handling: Proficient in More ❯

deep learning, probabilistic modeling, and/or NLP. Proficiency in programming languages such as Python, R, or Julia, with experience using ML frameworks (e.g., TensorFlow, PyTorch, Scikit-learn). Familiarity with biological datasets such as genomic, transcriptomic, proteomic, or imaging data. Experience working with large-scale datasets and cloud More ❯

you will bring: Essential: 5+ years of experience in data science, machine learning, or AI innovation. Strong coding skills in Python (e.g., Pandas, NumPy, TensorFlow, PyTorch) and SQL. Proven experience deploying ML models in production environments. 3+ years in a leadership or mentorship role within AI or data teams. More ❯

as well as cloud-based data storage solutions (e.g., AWS S3, Google Cloud Storage). Experience with AI/ML tools and frameworks (e.g., TensorFlow, PyTorch) and integrating data pipelines with these tools. Familiarity with containerization technologies (e.g., Docker, Kubernetes) and cloud platforms (e.g., AWS, GCP, Azure). Strong More ❯

learning methodologies, including supervised and unsupervised learning on image and tabular data. Familiarity with some of the latest AI frameworks and libraries, such as TensorFlow, PyTorch, Keras, etc Programming skills : Experience with scripting languages such as Python for data analysis and machine learning applications and software development Data management More ❯

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 ❯