26 to 50 of 287 TensorFlow Jobs in England

orchestration frameworks, context and memory management, and interoperability protocols such as MCP Experience with machine learning frameworks and data science packages such as PyTorch, TensorFlow, scikit‐learn, NumPy, pandas, SciPy, and statsmodels Experience deploying to AWS, including services such as SageMaker and Bedrock, and operating production large language model ...

would be highly beneficial: - Machine Learning and AI Engineering- Generative AI and Large Language Models- Prompt engineering and context engineering- scikit-learn, PyTorch or TensorFlow- LangChain or similar AI frameworks- Cloud data platforms and services across AWS, Azure or GCP- Data warehouses and modern data platforms- Big data ...

benchmarking and LLM performance evaluation (accuracy, latency, throughput). Hands‐on coding skills in Python, and familiarity with ML libraries and frameworks (PyTorch, TensorFlow, Hugging Face). Bachelor's or master's degree in Computer Science, Data Science, Engineering, or related field. Must be available to travel as needed ...

models to production and supporting them post-deployment. Strong Python programming skills, including object-oriented design and proficiency with key ML libraries (e.g., PyTorch, TensorFlow, Scikit-Learn). Solid understanding of probability and statistical modeling to support robust model development and interpretation. Experience with cloud platforms (especially Azure ...

vision, NLP/LLMs, multimodal AI, self-supervised learning, reinforcement learning, time-series analytics or foundation models. Experience with AI frameworks and libraries: PyTorch, TensorFlow, scikit-learn, Hugging Face Transformers; OpenCV for vision applications. Strong understanding of experimental design, statistical evaluation, benchmarking and model validation. Experiment tracking and reproducibility ...

track record of building and maintaining production‐quality systems. Expert‐level Python experience with numerical, statistical, or ML libraries (e.g. NumPy, pandas, PyTorch, JAX, TensorFlow). Deep understanding of statistical modelling, optimisation, or machine‐learning techniques. Experience building and operating backend systems and data pipelines in a cloud environment ...

developing technical teams. Strong client-facing communication skills, with the ability to engage senior stakeholders and lead technical discussions. Desirable Experience Experience with PyTorch, TensorFlow or other machine learning frameworks. Knowledge of LLM fine-tuning, model distillation and optimisation techniques. Experience with vector databases, semantic search, knowledge graphs ...

Strong programming skills in Python and experience with SQL and large-scale data processing technologies. Experience with modern machine learning frameworks such as PyTorch, TensorFlow, scikit-learn, or equivalent technologies. Strong understanding of statistical analysis, experimentation, hypothesis testing, model evaluation, and performance measurement. Experience working with large volumes ...

continuous improvement. Essential Skills and Experience Python programming skills for AI/ML development. Experience with at least one major ML framework (e.g. PyTorch, TensorFlow, scikit-learn). Experience building and maintaining end-to-end ML pipelines (data ingestion, pre-processing, training, evaluation, deployment) and deployment to production environments. ...

connect operational bottlenecks to strategic AI solutions. Software/Data Engineering: Python proficiency, API design, SQL, data integration, and ML/AI libraries (PyTorch, TensorFlow, scikit-learn, XGBoost, Hugging Face Transformers). Agentic AI Systems: Hands-on experience with agentic AI setups including LLM orchestration, tool use/function ...

datasets to generate actionable insights that inform business and product decisions Desirable: Hands-on coding and prototyping experience in AI/ML development (Python, TensorFlow, PyTorch) Experience with proof-of-concept development and technical validation of new AI technologies Background in data science or machine learning engineering with ...

projects end-to-end. Hands-On & Architectural Expertise: Strong software engineering foundations across the modern AI stack: Classical ML & Stats: Classical ML techniques (TensorFlow, PyTorch, scikit-learn), forecasting, and feature engineering. Generative AI & Agents: RAG, tool-calling, orchestration, guardrails, LLM-based agentic architectures, and fine-tuning. Cloud & MLOps: Production ...

integrations — with a strong focus on GenAI, NLP, computer vision, and multimodal AI applications. Leverage deep knowledge of AI/ML frameworks (e.g., PyTorch, TensorFlow, Hugging Face) and enterprise architecture best practices (e.g., microservices, APIs, cloud‐native design). AI & Data Platform Architecture/Deployment: Architect robust, secure ...

diff‐in‐diff, IV, matching) where randomization is impractical Fluency in Python and core data/ML libraries (pandas, NumPy, scikit‐learn, PyTorch or TensorFlow), combined with solid software engineering practices (clean code, testing, version control, code review) Proficient with large‐scale data: strong SQL skills and familiarity with ...

LLMs, NLP, or computer vision projects Knowledge of AWS, Azure, or GCP Familiarity with Docker, APIs, or Git workflowsFamiliarity with frameworks such as PyTorch, TensorFlow, or Scikit-learn Internship, university project, or personal portfolio related to AI/ML What’s on Offer Competitive graduate salary package Company stock ...

experience training, deploying, and maintaining machine learning models in production environments Proficiency in Python and relevant AI/ML libraries (e.g. scikit‐learn, TensorFlow, PyTorch) Experience with MLOps practices and tools for managing the machine learning lifecycle Experience building and deploying Generative AI applications, including familiarity with LLMOps Exposure ...

experience in a senior-level DevOps, MLOps, or related infrastructure-focused engineering role. Strong proficiency in Python and familiarity with ML frameworks such as TensorFlow or PyTorch. Deep experience with cloud platforms (AWS, GCP, or Azure) and container orchestration tools (Docker, Kubernetes). Solid understanding of CI/ ...

resiliency and security expectations; experience coaching engineers on safe, compliant adoption. Good understanding of data structures, algorithms, and practical machine learning frameworks (e.g., TensorFlow, PyTorch, Scikit-Learn). Proficiency in automation, continuous delivery (CI/CD), and cloud-native development (preferably AWS). Hands-on practical experience delivering system ...

Experience optimising dataframe code, e.g. in Pandas or ideally Polars Experience of machine learning techniques and related libraries and frameworks e.g. scikit-learn, Pytorch, Tensorflow etc Experience deploying and serving ML models in production, including model monitoring and real-time inference Experience in scientific computing with other languages & frameworks ...

Data Science, Machine Learning, or related field. Experience building and deploying agentic AI applications in production environments. Expertise with ML frameworks such as PyTorch, TensorFlow, and scikit‐learn. Proficiency in Python; experience writing comprehensive tests and building evaluation harnesses for agents and prompts. Hands‐on experience with agent frameworks ...

Data Science, Machine Learning, or related field. Experience building and deploying agentic AI applications in production environments. Expertise with ML frameworks such as PyTorch, TensorFlow, and scikit-learn. Proficiency in Python; experience writing comprehensive tests and building evaluation harnesses for agents and prompts. Hands‐on experience with agent frameworks ...

practices, covering the full cycle from design, experimentation, deployment, to monitoring and maintenance of machine learning models. Expertise in machine learning frameworks such as TensorFlow, PyTorch, PyTorch Lightning, or Scikit-learn. Proficiency in Python with a strong emphasis on code quality and reliability through comprehensive testing. Extensive experience with ...

scalability, security, and compliance. Lead technical reviews and provide guidance on complex AI engineering challenges. Technical Expertise: Deep expertise in AI/ML frameworks—TensorFlow, PyTorch, Scikit‐Learn, Transformers—cloud platforms (AWS, Azure, GCP), and modern software engineering practices. Strong background in deep learning, natural language processing, computer vision ...

resiliency and security expectations; experience coaching engineers on safe, compliant adoption. Good understanding of data structures, algorithms, and practical machine learning frameworks (e.g., TensorFlow, PyTorch, Scikit-Learn). Proficiency in automation, continuous delivery (CI/CD), and cloud-native development (preferably AWS). Hands-on practical experience delivering system ...

evaluation pipelines Experience in data and system engineering for large-scale model workflows Proven experience with deep learning frameworks and usage of DL libraries (TensorFlow/PyTorch) Fluent with at least one of the following tools: Cursor, Windsurf, Trae, Gemini CLI, Claude Code, or Codex (or similar) Experience ...