1 to 25 of 138 Permanent TensorFlow Jobs in the UK

experience NLP and Conversational AI development Model training, testing and evaluation Prompt Engineering and AI workflow optimisation Programming & Frameworks Strong Python development skills PyTorch TensorFlow Scikit-Learn LangChain LangGraph Hugging Face FastAPI REST APIs Data Technologies SQL NoSQL Databases Data Modelling ETL Development Data Pipeline Engineering Vector Databases such ...

Technical Expertise: Strong Python skills with the ML stack: NumPy, pandas, scikit-learn Hands-on experience with at least one deep learning framework (PyTorch, TensorFlow, JAX) Solid grounding in core ML—supervised, unsupervised, evaluation, regularisation, statistics Production ML experience—deploying, serving and monitoring models at scale LLM and generative ...

custom AI assistants/agents). Strong proficiency in Python for AI/ML development, including use of common ML and data libraries (e.g. TensorFlow/PyTorch, scikit-learn, pandas, NumPy). Proven experience integrating AI services with enterprise systems via APIs and event-driven architectures. Practical experience with ...

Proficiency Machine learning algorithms: linear regression, logistic regression, decision trees, random forests, support vector machines, neural networks Data science tools: NumPy, SciPy, Pandas, Matplotlib, TensorFlow, Keras Cloud computing platforms: AWS, Azure, GCP Natural language processing: transformer models, attention mechanisms, word embeddings Computer vision: convolutional neural networks, recurrent neural networks ...

experience in managing, coaching, and developing junior members of a team and wider community. Desirable Demonstrable experience with modern deep learning frameworks (e.g. PyTorch, TensorFlow), fine‐tuning or distillation of LLMs (e.g, GPT, Llama, Claude, Gemini), machine learning libraries (e.g. scikit‐learn, XGBoost). Experience with data storage ...

considerations. \n\n \n Strong interpersonal skills and team working. \n\n DESIRABLE: \n \n Demonstrable experience with modern deep learning frameworks (e.g. PyTorch, TensorFlow), fine-tuning or distillation of LLMs (e.g., GPT, Llama, Claude, Gemini), machine learning libraries (e.g. scikit-learn, XGBoost). \n\n \n Experience with ...

developing junior members of a team and wider community. \n\n DESIRABLE: \n \n Demonstrable experience with modern deep learning frameworks (e.g. PyTorch, TensorFlow), fine-tuning or distillation of LLMs (e.g, GPT, Llama, Claude, Gemini), machine learning libraries (e.g. scikit-learn, XGBoost). \n\n \n Experience with data ...

developing junior members of a team and wider community. \n\n DESIRABLE: \n \n Demonstrable experience with modern deep learning frameworks (e.g. PyTorch, TensorFlow), fine-tuning or distillation of LLMs (e.g. GPT, Llama, Claude, Gemini), machine learning libraries (e.g. scikit-learn, XGBoost). \n\n \n Experience with data ...

strong understanding of ML and deep learning methods and large language models.Extensive experience with ML/DL toolkits and libraries (e.g., Transformers, Hugging Face, TensorFlow, PyTorch, NumPy, scikit-learn, pandas).Demonstrated leadership in proposing and delivering AI/ML and GenAI solutions; ability to drive technical direction and influence ...

Experience working with Large Language Models LLM seg GPT Gemini opensource models Knowledge of prompt engineering finetuning and LLM evaluation Familiarity with AIML frameworks TensorFlow PyTorch Hugging Face Experience building APIs and microservices Fast API Flask Understanding of MLOps practices monitoring model lifecycle management Preferred Qualifications Experience with ...

Machine Learning, Generative AI, Natural Language Processing, Advanced Analytics, and ideally Computer Vision. Excellent Python development skills with frameworks such as pandas, scikit-learn, TensorFlow or PyTorch, and LangChain. Experience with cloud AI services including AWS Bedrock, Azure Machine Learning, or Google Cloud AI Platform. Good understanding of data ...

Language Processing, Generative AI, and advanced analytical techniques • Proficiency in Python and experience with AI and data science frameworks such as pandas, scikit-learn, TensorFlow, PyTorch, or LangChain • Experience developing and deploying AI models into production environments • Solid understanding of data engineering principles, including data preparation, integration, and deployment ...

Vetting: Active SC Clearance and British Citizenship are mandatory for this consultancy role. Core Tech: Solid professional experience with Python and frameworks like PyTorch, TensorFlow, or Scikit-Learn. GenAI: Hands-on experience developing LLM-based applications, RAG pipelines, and prompt engineering. Infrastructure: Experience deploying applications in cloud environments ...

Experience Required \n Essential \n \n Strong Python programming and hands-on experience with core ML/AI libraries (for example scikit-learn, TensorFlow, PyTorch). \nPractical experience developing, training and evaluating machine learning, NLP and predictive models.Experience deploying AI/ML in the cloud, particularly Microsoft Azure (Azure ...

bias/fairness and emerging regulations. Machine Learning Mastery – profound understanding of ML principles, algorithms, frameworks, and training pipelines. Technical Proficiency – programming in Python, TensorFlow, PyTorch or similar; modern LLM/agent frameworks; cloud AI platforms (Amazon Bedrock, Azure OpenAI/AI Foundry, Google Vertex AI); vector databases; containerization ...

high-throughput file systems (e.g. Everpure, WEKA, VAST, NetApp) sized for training and checkpointing workloads. AI Software, MLOps & Generative AI ML frameworks: PyTorch and TensorFlow at a working, hands-on level. Distributed training: Horovod, DeepSpeed, Megatron-LM, or equivalent multi-node training frameworks. Inference & serving: NVIDIA Triton, vLLM, TensorRT ...

deploying AI applications in large scale production environments. Experience managing data science teams and couching team members Proficiency in Python and ML frameworks (PyTorch, TensorFlow, scikit-learn). Hands-on experience with agentic frameworks (LangChain, CrewAI, AutoGen, LangGraph, ADK). Experience with generative models (transformers, GANs/VAEs; diffusion ...

Google Cloud Platform, or Microsoft Azure)Knowledge of containerisation technologies like Docker and orchestration tools such as KubernetesExperience with AI/ML frameworks (e.g., TensorFlow, PyTorch, or Java-based ML libraries)Strong problem-solving and communication skills\n Preferred Qualifications \n \n Experience with NLP, computer vision, or recommendation ...

Python and SQL, with experience in data manipulation, model development, and analytical workflows. Hands‐on experience with machine learning frameworks such as scikit‐learn, TensorFlow, PyTorch, or similar. Strong experience with cloud platforms (AWS, Azure, or GCP) and building cloud‐native systems. Experience with modern data platforms such ...

large-scale production environments.Experience with MLOps practices and tools for managing the machine learning lifecycle.Proficiency in Python and machine learning frameworks such as PyTorch, TensorFlow, and scikit-learn.Strong understanding of data preprocessing, feature engineering, and evaluation techniques.Experience working with large, complex datasets and applying statistical analysis.Familiarity with cloud platforms ...

wider community. \n Must have active UK Government Security Clearance\n DESIRABLE: \n \n Demonstrable experience with modern deep learning frameworks (e.g. PyTorch, TensorFlow), fine-tuning or distillation of LLMs (e.g., GPT, Llama, Claude, Gemini), machine learning libraries (e.g. scikit-learn, XGBoost). \n\n \n Experience with data ...

agentic frameworks. Strong proficiency in programming languages such as Python, Java, or Go, along with experience integrating with relevant AI/ML frameworks (e.g., TensorFlow, PyTorch). Proven ability to translate complex business requirements into well‐defined, cloud‐optimized application architectures, scalable data models (e.g., relational, NoSQL, graph ...

record of leading ML/AI technical initiatives across multiple teams Strong experience with cloud platforms (AWS, Azure, GCP) Experience with ML frameworks (PyTorch, TensorFlow, scikit-learn) and Gen AI/Agentic frameworks (LangGraph, LangChain, VectorDBs, RAG) Understanding of responsible AI practices, including guardrails, hallucination mitigation, and output quality ...

systems for cost efficiency, performance and scalability against standard benchmarks.18. Stay ahead of developments in GenAI (e.g. LLMs, multimodal models), ML frameworks (e.g. PyTorch, TensorFlow, Scikit-learn), orchestration tools (e.g. LangChain, LangFuse), model hubs. Taking responsibility for your own continuous professional development.19. Fostering a culture of responsible innovation … C#, Rust etc) Proficiency in at least one programming language (eg Python, Scala etc) plus SQL . Proficiency in ML libraries (e.g., TensorFlow, PyTorch, Hugging Face). Ability to set up and use APIs and integrate AI components into existing systems and workflows. Ability to collaborate across disciplines such ...

augmented generation, tool/function calling, agentic workflows), including evaluation and safety patterns. Expertise with machine learning frameworks and data science packages (e.g., PyTorch, TensorFlow, Scikit‐Learn, NumPy, Pandas, SciPy, statsmodels). Experience deploying to AWS (e.g., SageMaker, Bedrock) and operating production workloads with attention to cost, performance, security ...