26 to 50 of 276 TensorFlow Jobs in England

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 ...

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 ...

production. Strong technical knowledge, including proficiency in Python and experience with core data science and ML libraries (e.g., scikit-learn, pandas, PyTorch or TensorFlow). Practical experience with Databricks, including MLflow for experiment tracking and model management, and Spark-based data processing. Familiarity with Generative AI concepts and tooling ...

Physics, Computer Science, or a related field, or equivalent education and industry experience. Advanced Python proficiency with Pandas, NumPy, scikit-learn, and PyTorch or TensorFlow; SQL and practical data preparation skills. Strong statistics, experimental design, hypothesis testing, ML validation, and applied classification, regression, ranking, clustering, forecasting, and anomaly detection ...

concepts clearly Strong analytical thinking, problem-solving capability, and exceptional attention to detail Desirable (Not Essential) Skills Natural Language Processing techniques Deep learning frameworks (TensorFlow, PyTorch) Generative AI tools/frameworks (LLMs, diffusion models) Experience building Python microservices (Flask, Docker) SQL and database systems Agile methodologies and version control ...

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 ...

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 ...

model packaging and release management, automated validation, monitoring, and lifecycle management Working knowledge of ML/DL frameworks and tooling (e.g. PyTorch/TensorFlow and the Python ML ecosystem) sufficient to collaborate effectively with data scientists and implement inference pipelines Experience working with complex, multi‐layered datasets (including imbalanced ...

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 ...

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 ...

many of the following: Hands-on experience developing and deploying ML models in Python using frameworks such as scikit-learn, XGBoost, PyTorch, or TensorFlow Strong experience with AWS ML services (SageMaker, Lambda, S3) in production environments Strong experiment design skills: hypothesis formulation, A/B testing methodology, and statistical ...

many of the following: Hands-on experience developing and deploying ML models in Python using frameworks such as scikit-learn, XGBoost, PyTorch, or TensorFlow Strong experience with AWS ML services (SageMaker, Lambda, S3) in production environments Strong experiment design skills: hypothesis formulation, A/B testing methodology, and statistical ...

retrieval-augmented generation, tool/function calling, structured outputs, and multi-step or agentic workflows Strong Python skills, including deep learning frameworks (PyTorch or TensorFlow), the Hugging Face ecosystem, and core data libraries (NumPy, Pandas, scikit-learn) Clear written and spoken communication for both technical and business audiences ...

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 ...

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 ...

Science Mathematics Software Engineering Or a related STEM field Core Skills & Competencies Technical Skills Programming proficiency in Python and common ML libraries such as: TensorFlow, PyTorch, or similar Experience with Jupyter Notebooks and version control (Git/GitHub) Basic understanding of supervised/unsupervised learning, neural networks, or clustering ...

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 ...

platforms Excellent command of English – both written and spoken (international client communication, presentations), Expertise in at least one of the following domains: Experience with TensorFlow, PyTorch, XGBoost, LightGBM, Proficiency with Git, Linux, Docker, MLflow, Airflow, AWS/GCP/Azure, Solid SQL and data visualization skills. Additional Information Nice ...

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 ...

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 ...

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 ...

projects end-to-end. Hands-On & Architectural Expertise: Strong software engineering foundations across the modern AI stack: Classic 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 ...

discipline — or equivalent professional experience Preferred Skills and Experience Familiarity with observability instrumentation for AI systems (OpenTelemetry, Prometheus) Experience with AI/ML frameworks (TensorFlow, PyTorch) and the Hugging Face/open‐source AI ecosystem Experience with image understanding and OCR Working knowledge of policy‐as‐code (OPA/ ...

communication skills. Desirable Experience Machine Learning model development and training. LLMs, transformers, RAG and Agentic AI. LangChain, LangGraph or similar AI orchestration frameworks. PyTorch, TensorFlow, Scikit-learn or Hugging Face. Vector databases, embeddings and model evaluation. NLP, Computer Vision or multimodal AI. Edge AI, AI safety, security or explainability. ...

experience training, deploying, and maintaining machine learning models in production Proficiency in Python and relevant AI/ML libraries (such as 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 ...