1 to 25 of 83 TensorFlow Jobs in England

experience (3–5+ years) as a Machine Learning Engineer , Data Scientist , or similar role. Strong programming skills in Python (experience with libraries such as TensorFlow, PyTorch, scikit-learn, pandas, NumPy). Solid understanding of machine learning algorithms , statistical modelling , and deep learning architectures . Hands-on experience with MLOps ...

Required Experience & Skills AI/Technical Strong experience building and deploying machine learning and AI solutions in production. Hands‐on experience with: Python (PyTorch, TensorFlow, scikit‐learn) Data engineering tools (SQL, Spark, Airflow or similar) LLMs, NLP, and document intelligence (e.g. RAG, embeddings) Experience with cloud platforms (AWS, Azure ...

work in the UK (we are unable to offer visa sponsorship for this role) Desirable (Not Essential): Familiarity with deep learning frameworks (e.g. TensorFlow, PyTorch) Exposure to cloud platforms (AWS, GCP, or Azure) Experience with experimental design, research methods, or academic publishing Understanding of MLOps, version control ...

GenAI Ecosystem Lead the design and deployment of scalable AI solutions across Python, .NET, and cloud-native platforms Drive adoption of advanced frameworks (PyTorch, TensorFlow, Hugging Face, LangChain) Oversee integration of LLMs (OpenAI, Anthropic, Gemini, Mistral) via enterprise platforms (Azure OpenAI, Vertex AI) Implement RAG architectures and manage vector ...

professional experience delivering advanced AI/ML solutions in industry or engineering environments. Strong expertise in Python and AI/ML libraries: PyTorch, TensorFlow, Scikit‐Learn, Keras, NumPy, Pandas, JAX, XGBoost, PyTorch Geometric, OpenCV, Transformers, LangChain, Pinecone . Proven hands‐on experience deploying models in production and building scalable ...

Power BI. Published work, patents or conference presentations related to AI or data science in finance. Technical Skills Programming: Python (pandas, scikit‐learn, TensorFlow/PyTorch), R, SQL, Jupyter notebooks and version control (Git). Machine Learning: regression, classification, clustering, tree‐based models, neural networks, MLOps practices and model ...

systems Stay up to date with the latest advancements in machine learning and AI technologies Required Skills & Experience Strong programming skills in Python (e.g., TensorFlow, PyTorch, Scikit-learn) Experience deploying ML models using cloud platforms (AWS, Azure, or GCP) Solid understanding of machine learning algorithms, data structures, and software ...

date with emerging machine learning technologies and best practices Skills and Experience • Strong programming skills in Python • Experience with machine learning frameworks such as TensorFlow, PyTorch, or Scikit-learn • Experience working with SQL and large datasets • Familiarity with data pipelines, feature engineering, and model optimisation • Understanding of MLOps practices ...

maximum scalability and cost-efficiency. Insurance Domain experience is added advantage. Your Technical Toolkit AI/ML: Expert proficiency in Python , PyTorch/TensorFlow, and GenAI frameworks like LangChain, LlamaIndex, or CrewAI . Data Architecture: Hands-on experience with Vector Databases (e.g., Pinecone, Milvus, Weaviate) and SQL/NoSQL ...

maximum scalability and cost-efficiency. Insurance Domain experience is added advantage. Your Technical Toolkit AI/ML: Expert proficiency in Python , PyTorch/TensorFlow, and GenAI frameworks like LangChain, LlamaIndex, or CrewAI . Data Architecture: Hands-on experience with Vector Databases (e.g., Pinecone, Milvus, Weaviate) and SQL/NoSQL ...

domain-specific use cases Retrieval-Augmented Generation (RAG) fundamentals and context engineering Hands-on or strong exposure to Python and common AI libraries (PyTorch, TensorFlow). Familiarity with: LLMs (OpenAI, Anthropic, Hugging Face, LLaMA models) Vector databases (Pinecone, Weaviate, FAISS , Qudrant) Agentic AI frameworks (exposure to LangGraph, AutoGen, CrewAI ...

incl software development with a strong track record of delivering business value Proficiency in Python and ML/DL frameworks (e.g., scikit-learn, PyTorch, TensorFlow) Experience with AI/ML tools (e.g., Jupyter, MLflow, Vertex AI, Azure ML, Amazon SageMaker Experience of creating delivery client-facing proof of concepts ...

Profile Essential skills/knowledge/experience: Proficiency in Python programming. Foundational understanding of machine learning concepts and algorithms. Familiarity with frameworks such as TensorFlow or PyTorch. Basic knowledge of Natural Language Processing (NLP) techniques. Understanding of neural networks and deep learning fundamentals. Exposure to Generative AI concepts ...

visualization tools). Published research, patents, or conference presentations in AI or data science related to finance. Technical Skills Programming: Python (pandas, scikit‐learn, TensorFlow/PyTorch), R, SQL, notebooks, Git. Machine Learning: regression, classification, clustering, tree‐based models, neural networks; MLOps, model deployment, automated testing. Data Platforms: relational ...

users) machine learning solutions for personalizing recommendations. Hands-on experience building training frameworks and/or serving large-scale models using tools such as Tensorflow or PyTorch is a plus. You stay up-to-date with the state-of-the-art open source infrastructure solutions applicable to designing ...

Semantic Search techniques & tools. Experience in writing robust and efficient code in Python. Experience in using tools relevant to deep learning like PyTorch, TensorFlow, LangChain. Experience in designing & implementing key MLOps capabilities & frameworks in delivering robust train, test, monitor and improve lifecycles for AI/ML model deployments. Experience ...

Semantic Search techniques & tools. Experience in writing robust and efficient code in Python. Experience in using tools relevant to deep learning like PyTorch, TensorFlow, LangChain. Experience in designing & implementing key MLOps capabilities & frameworks in delivering robust train, test, monitor and improve lifecycles for AI/ML model deployments. Experience ...

queries using SQL. Familiarity with data manipulation libraries (Pandas, NumPy), Understanding of statistics and probability. Hands-on experience with ML libraries like Scikit-learn, TensorFlow, or PyTorch. Preferred Skills: Hands on experience in coding (mandatory python and SQL or C++). Understanding of Generative AI, Computer Vision cloud technology ...

queries using SQL. Familiarity with data manipulation libraries (Pandas, NumPy), Understanding of statistics and probability. Hands-on experience with ML libraries like Scikit-learn, TensorFlow, or PyTorch. Preferred Skills: Hands on experience in coding (mandatory python and SQL or C++). Understanding of Generative AI, Computer Vision cloud technology ...

core data science libraries: Pandas, NumPy, and SciPy . Machine Learning: Deep, practical experience with popular ML frameworks and libraries: scikit-learn, TensorFlow, or PyTorch . Statistics & Math: Strong foundation in statistical modeling , probability, hypothesis testing, regression analysis, and multivariate calculus/linear algebra for understanding model mechanics. Databases ...

working as a data scientist (or similar role). Expert proficiency of Python and experience using SQL, alongside using common ML/AI packages (TensorFlow, PyTorch, XGBoost, etc.). Familiarity with statistical (e.g. GLM, GAMs) and deep learning techniques (e.g. neural networks, transformers, diffusion models, etc.). Comfortable designing ...

SparkSQL in data or ML-focused roles. Strong understanding of machine learning concepts and experience using common ML libraries such as scikit‐learn, TensorFlow or PyTorch, alongside packages such as NumPy and Pandas. Knowledge of natural language processing techniques and API integration patterns for ML services. Experience delivering projects ...

distributed environment. LLMs: Understanding of LLM architectures, pre and/or post-training, evaluations and inference. Programming languages: Proficiency in Python using PyTorch/TensorFlow/JAX framework. Cloud-native technologies: Experience in developing and deploying in cloud platforms (e.g., AWS, GCP or Azure), an understanding of containerisation (e.g. ...

LLMs: Deep understanding of LLM architectures, pre and/or post-training, evaluations and inference. Programming languages: Excellent proficiency in Python using PyTorch/TensorFlow/JAX framework. Customer facing: Experience working directly with customers to solve applied problems, including product integration. Cloud-native technologies: Experience in developing ...

/ML engineering or architecture roles Proven experience in the healthcare or life sciences domain Strong knowledge of machine learning frameworks (e.g., TensorFlow, PyTorch) Experience with healthcare data standards (e.g., HL7, FHIR) Familiarity with cloud platforms (AWS, Azure, or GCP) Understanding of data privacy, security, and regulatory requirements ...