26 to 50 of 281 TensorFlow Jobs in England

science roles. Proven track record of building, deploying, and maintaining production-grade AI models and pipelines. Strong proficiency in Python, R, and ML frameworks (TensorFlow, PyTorch, Scikit-learn). Experience with cloud platforms and ML infrastructure (AWS SageMaker, MLflow). Practical understanding of monitoring, logging, and CI/CD. ...

shipping 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 and/ ...

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 ...

Experience Requirements BSc in Machine Learning, Data Science, Computer Science, Mathematics or related field. Experience coding in Python and associated ML packages (HuggingFace, TensorFlow, PyTorch). Have an established track record of delivering ML solutions to customers and internal stakeholders. Demonstrate deep understanding of AI/ML algorithms ...

architecturesTrack record of leading ML/AI technical initiatives across multiple teamsStrong 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 ...

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 ...

Flows). Multimodal Pipelines – Prior exposure to conversational voice pipelines or multimodal integrations via hyperscaler services. Advanced AI/ML Frameworks – Exposure to frameworks (TensorFlow, PyTorch), MLOps practices, and cloud AI platforms like Google Vertex AI or AWS Sagemaker. Education – BS in Computer Science, Engineering, Data Science, or equivalent ...

solutions in Python Solid understanding of the Python ML ecosystem including libraries such as NumPy, pandas, and scikit learn, with exposure to PyTorch or TensorFlow Experience building and deploying containerised services and APIs Working knowledge of SQL and data driven application development Hands on experience with at least ...

delivering AI/ML projects end-to-end in production environments Strong Python skills with hands-on use of ML libraries like Scikit-learn, TensorFlow, PyTorch, or Hugging Face Solid understanding of machine learning fundamentals and performance evaluation techniques Experience working in cloud platforms (AWS, GCP, or Azure) 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 ...

related field. Strong software engineering skills: clean code, testing, debugging, version control, and system design. Proficiency in Python with experience in ML frameworks (PyTorch, TensorFlow, or JAX). Hands‐on experience with cloud platforms (AWS, GCP, or Azure) and containerisation (Docker, Kubernetes). Solid understanding of ML fundamentals (model ...

skills (Python, SQL or similar) Experience building and maintaining data pipelines Working with structured and unstructured data Desirable Experience with machine learning frameworks (e.g. TensorFlow, PyTorch, scikit-learn) Exposure to Generative AI tools/frameworks (e.g. LLMs, LangChain) Experience with cloud platforms (Azure, AWS, or GCP) Familiarity with data ...

deep learning. Proficiency in data manipulation, feature engineering, and model evaluation. Strong programming skills in languages such as Python and experience with libraries like TensorFlow, PyTorch, or scikit‐learn. Excellent communication skills and the ability to collaborate effectively within cross‐functional teams. A passion for continuous learning and staying ...

SciPy. Predictive & Deep Learning: Deep knowledge of machine learning workflows in scikit‐learn and at least one deep learning framework such as PyTorch or TensorFlow . Generative AI: Practical experience with LLM orchestration (e.g., LangChain) and vector databases for RAG workflows. Cloud & DevOps: Professional experience with AWS/SageMaker ...

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 ...

record delivering production AI/ML and GenAI at enterprise scale — real impact, not just prototypes Expert Python with hands-on experience in PyTorch, TensorFlow, LangChain, LangGraph, RAG pipelines, and LLMs Solid MLOps/LLMOps fundamentals: CI/CD for ML, model governance, and evaluation frameworks Broad cloud experience ...

MLflow, Azure ML, Azure DevOps, or similar tools. Strong programming skills in Python and familiarity with common ML/AI libraries, including Scikit-learn, TensorFlow, and Keras. Experience implementing machine learning and large language models, including deployment, monitoring, and retraining. Familiarity with software engineering guidelines, including version control ...

Agentic AI systems LangChain, LangGraph, LlamaIndex, Semantic Kernel, or similar frameworks RAG pipelines and vector databases AI agents and multi-agent orchestration Python, PyTorch, TensorFlow, Scikit-learn Cloud AI platforms such as AWS, Azure, or GCP Production deployment, MLOps, and scalable AI infrastructure API integration and workflow automation Bonus ...

machine learning, deep learning, and optimisation Hands-on experience training, evaluating, and deploying ML models in real-world systems Proficiency with PyTorch (preferred) or TensorFlow; familiarity with the Hugging Face ecosystem Experience with audio or speech models and frameworks. Experience building and maintaining end-to-end ML pipelines ...

Experience in working with AWS and GCP services for various activities in the data science workflow. Working knowledge of deep learning frameworks such as TensorFlow and PyTorch. Broad understanding of Transfer Learning Models and its application to alternative data in Finance. Good understanding of NLP modelling concepts and ability ...

decision-making around cloud architecture, scalability, and system design Help establish engineering best practices in a fast-moving early-stage environment Tech Stack Python TensorFlow/PyTorch LLM frameworks (LangChain, LangGraph, or similar agentic AI tooling) AWS/Azure cloud platforms (including AI services such as Bedrock) Data engineering ...

What You’ll Bring Strong Python coding skills. Hands‐On AI/ML Expertise: Built and deployed machine learning models using frameworks like PyTorch, TensorFlow, or scikit‐learn. LLM Expertise: Experienced in working with large language models, including prompt engineering, RAG, fine‐tuning, agents, evaluation, and safety considerations ...

advantageous. Experience with Azure AI Search (hybrid search, indexing), vector/embedding concepts, and GenAI evaluation/guardrails; familiarity with ML frameworks (for example TensorFlow) is a plus. Experience with complementary data prep/automation tooling (for example Alteryx or Power Platform). Experience with data warehouse automation tools ...

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 ...