1 to 25 of 115 TensorFlow Jobs in London

degree in a STEM field: Statistics, Mathematics, Computer Science, Engineering, or similar. Programming proficiency: Strong experience with Python and SQL; familiarity with libraries such as Pandas, NumPy, Scikit-learn, TensorFlow, or PyTorch. Machine learning expertise: Hands-on experience in supervised and unsupervised learning, with exposure to NLP, computer vision, or deep learning a plus. Data visualisation: Proficiency in Tableau More ❯

degree in a STEM field: Statistics, Mathematics, Computer Science, Engineering, or similar. Programming proficiency: Strong experience with Python and SQL; familiarity with libraries such as Pandas, NumPy, Scikit-learn, TensorFlow, or PyTorch. Machine learning expertise: Hands-on experience in supervised and unsupervised learning, with exposure to NLP, computer vision, or deep learning a plus. Data visualisation: Proficiency in Tableau More ❯

Statistics, or a related field. 6+ years of experience in ML Engineering or Data Science (finance, fintech, or treasury a plus). Proficiency in Python-including pandas, scikit learn, TensorFlow/PyTorch, LightGBM/XGBoost-and experience with SQL. Hands on experience with cloud ML platforms (AWS SageMaker, Azure ML, or Google AI Platform). Solid understanding of software More ❯

and collaboration skills Full right to 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 (Git), or containerisation (e.g. Docker) Benefits More ❯

and collaboration skills Full right to 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 (Git), or containerisation (e.g. Docker) Benefits More ❯

and collaboration skills Full right to 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 (Git), or containerisation (e.g. Docker) Benefits More ❯

and collaboration skills Full right to 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 (Git), or containerisation (e.g. Docker) Benefits More ❯

optimisation * Experience developing & deploying productionised Machine Learning applications on a cloud platform (GCP ideal, AWS & Azure also acceptable) * Experience with common Python packages for Machine Learning - examples include PyTorch, TensorFlow, XGBoost, scikit-learn, SciPy, NumPy, pandas, etc. * Strong knowledge of SQL and its use for data preparation & feature engineering * Understanding of & practical experience with implementing MLOps principals - including automated More ❯

up to date with the latest advancements in deep learning, computer vision, and related technologies. Key Skills & Experience Strong hands on experience with Computer Vision frameworks (e.g., OpenCV, PyTorch, TensorFlow). Proficiency in Python and ML/DL libraries (NumPy, Pandas, scikit-learn). Proven track record of building and deploying ML models in production environments. Knowledge of MLOps More ❯

up to date with the latest advancements in deep learning, computer vision, and related technologies. Key Skills & Experience Strong hands on experience with Computer Vision frameworks (e.g., OpenCV, PyTorch, TensorFlow). Proficiency in Python and ML/DL libraries (NumPy, Pandas, scikit-learn). Proven track record of building and deploying ML models in production environments. Knowledge of MLOps More ❯

Stay up-to-date with the latest ML research and tools. Required Skills & Experience Strong proficiency in Python and its ML/data libraries (e.g., NumPy, pandas, scikit-learn, TensorFlow or PyTorch). Hands-on experience with Amazon SageMaker , including training, tuning, and deploying models. Solid understanding of machine learning algorithms and statistical methods. Experience with cloud platforms (AWS More ❯

up to date with the latest advancements in deep learning, computer vision, and related technologies. Key Skills & Experience Strong hands on experience with Computer Vision frameworks (e.g., OpenCV, PyTorch, TensorFlow). Proficiency in Python and ML/DL libraries (NumPy, Pandas, scikit-learn). Proven track record of building and deploying ML models in production environments. Knowledge of MLOps More ❯

up to date with the latest advancements in deep learning, computer vision, and related technologies. Key Skills & Experience Strong hands on experience with Computer Vision frameworks (e.g., OpenCV, PyTorch, TensorFlow). Proficiency in Python and ML/DL libraries (NumPy, Pandas, scikit-learn). Proven track record of building and deploying ML models in production environments. Knowledge of MLOps More ❯

and techniques in deep learning. Required Skills & Experience: Proven experience in developing and deploying deep learning models in production. Strong proficiency in Python and deep learning libraries (e.g., PyTorch, TensorFlow, Keras). Solid understanding of neural network architectures (CNNs, RNNs, Transformers, etc.). Experience with cloud platforms (AWS, GCP, or Azure) and containerization (Docker, Kubernetes). Familiarity with MLOps More ❯

and techniques in deep learning. Required Skills & Experience: Proven experience in developing and deploying deep learning models in production. Strong proficiency in Python and deep learning libraries (e.g., PyTorch, TensorFlow, Keras). Solid understanding of neural network architectures (CNNs, RNNs, Transformers, etc.). Experience with cloud platforms (AWS, GCP, or Azure) and containerization (Docker, Kubernetes). Familiarity with MLOps More ❯

and techniques in deep learning. Required Skills & Experience: Proven experience in developing and deploying deep learning models in production. Strong proficiency in Python and deep learning libraries (e.g., PyTorch, TensorFlow, Keras). Solid understanding of neural network architectures (CNNs, RNNs, Transformers, etc.). Experience with cloud platforms (AWS, GCP, or Azure) and containerization (Docker, Kubernetes). Familiarity with MLOps More ❯

and techniques in deep learning. Required Skills & Experience: Proven experience in developing and deploying deep learning models in production. Strong proficiency in Python and deep learning libraries (e.g., PyTorch, TensorFlow, Keras). Solid understanding of neural network architectures (CNNs, RNNs, Transformers, etc.). Experience with cloud platforms (AWS, GCP, or Azure) and containerization (Docker, Kubernetes). Familiarity with MLOps More ❯

core ML concepts (classification, time-series, statistical modeling) and their real-world tradeoffs. Fluency in Python and commonly used ML libraries (e.g. pandas, scikit-learn; experience with PyTorch or TensorFlow is a plus). Experience with model lifecycle management (MLOps), including monitoring, retraining, and model versioning. Ability to work across data infrastructure, from SQL to large-scale distributed data More ❯

developing underwriting or behavioural models for credit extension Desired: Master's degree in Data Science/Machine Learning or related discipline Knowledge of Deep Learning frameworks, ideally Keras/Tensorflow Familiarity with software version control (GitHub, bitbucket) Knowledge of Tableau Ability to comprehend research papers and possibly apply their solutions Credit card industry knowledge What's in it for More ❯

strategic value Qualifications Experience Extensive experience in data science, machine learning, or advanced analytics, ideally in a technical leadership role Proven expertise in Python and ML frameworks (e.g., PyTorch, TensorFlow, Scikit-learn) and experience across NLP, computer vision, and LLMs Strong statistical foundation, including A/B testing, causal inference, and experimental design Proficiency in SQL and working with More ❯

into production systems. Collaborate with data scientists, engineers, and product teams to define AI solutions. Ensure scalability, performance, and ethical AI practices. Required Skills & Experience: Strong experience in Python, TensorFlow, PyTorch, Scikit-learn or similar frameworks. Solid understanding of machine learning, deep learning, NLP, or computer vision. Hands-on with data engineering, model deployment (MLOps), and cloud platforms (AWS More ❯

into production systems. Collaborate with data scientists, engineers, and product teams to define AI solutions. Ensure scalability, performance, and ethical AI practices. Required Skills & Experience: Strong experience in Python, TensorFlow, PyTorch, Scikit-learn or similar frameworks. Solid understanding of machine learning, deep learning, NLP, or computer vision. Hands-on with data engineering, model deployment (MLOps), and cloud platforms (AWS More ❯

Anthropic, Mistral), embeddings, RAG, LangChain/LlamaIndex. Strong understanding of OpenAI for Business and custom GPT development , including enterprise integration and compliance guardrails. Proven engineering skills — Python (PyTorch/TensorFlow, JAX) , SQL/Spark, data wrangling, API integration. MLOps & deployment experience — MLflow, W&B, Docker/Kubernetes, CI/CD pipelines. Track record shipping real-world AI systems with More ❯

Anthropic, Mistral), embeddings, RAG, LangChain/LlamaIndex. Strong understanding of OpenAI for Business and custom GPT development , including enterprise integration and compliance guardrails. Proven engineering skills — Python (PyTorch/TensorFlow, JAX) , SQL/Spark, data wrangling, API integration. MLOps & deployment experience — MLflow, W&B, Docker/Kubernetes, CI/CD pipelines. Track record shipping real-world AI systems with More ❯

excellent understanding of key concepts in computer science (e.g. databases, software engineering practices, cloud computing - especially AWS) and data science (e.g. machine learning process) Excellent knowledge of Python includingPytorch, Tensorflow andSKLearn as well as initial knowledge of LangChain andRAGAS. Familiarity with CI/CD workflows is required and experience with containerisation and deployment using Docker/Kubernetes will be More ❯