1 to 25 of 409 TensorFlow Jobs in London

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 More ❯

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 More ❯

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 More ❯

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 More ❯

SQL, MongoDB Experience on general programming languages: Python, C++, Java, etc. Experience with deep learning, machine learning and NLP frameworks such as PyTorch (or TensorFlow), HuggingFace Transformer, Scikit-learn Experience with working in Linux A strong intuition for what makes products a joy to use Empathy for how different More ❯

with training and evaluating BERT-like models in real-world applications, especially in NLP or classification problems. Hands on experience with ML tools like TensorFlow, PyTorch etc. Experience with data science libraries such as NLTK, Scikit-learn, SciPy, (Sci)SpaCy etc. Excellent problem-solving and programming skills in Python More ❯

in developing and deploying machine learning models, with a strong focus on generative AI techniques. - Proficiency in programming languages such as Python, PyTorch, or TensorFlow, and experience with deep learning frameworks. - Strong background in natural language processing, computer vision, or multimodal learning. - Ability to communicate technical concepts to both More ❯

bidder, documented bids and face to face presentations. Experience of data science platforms (e.g. Databricks, Dataiku, AzureML, SageMaker) and machine learning frameworks (e.g. Keras, Tensorflow, PyTorch, scikit-learn) Cloud platforms – demonstrable experience of building and deploying solutions to Cloud (e.g. AWS, Azure, Google Cloud) including Cloud provisioning tools (e.g. More ❯

bidder, documented bids and face to face presentations. Experience of data science platforms (e.g. Databricks, Dataiku, AzureML, SageMaker) and machine learning frameworks (e.g. Keras, Tensorflow, PyTorch, scikit-learn) Cloud platforms – demonstrable experience of building and deploying solutions to Cloud (e.g. AWS, Azure, Google Cloud) including Cloud provisioning tools (e.g. More ❯

bidder, documented bids and face to face presentations. Experience of data science platforms (e.g. Databricks, Dataiku, AzureML, SageMaker) and machine learning frameworks (e.g. Keras, Tensorflow, PyTorch, scikit-learn) Cloud platforms – demonstrable experience of building and deploying solutions to Cloud (e.g. AWS, Azure, Google Cloud) including Cloud provisioning tools (e.g. More ❯

bidder, documented bids and face to face presentations. Experience of data science platforms (e.g. Databricks, Dataiku, AzureML, SageMaker) and machine learning frameworks (e.g. Keras, Tensorflow, PyTorch, scikit-learn) Cloud platforms – demonstrable experience of building and deploying solutions to Cloud (e.g. AWS, Azure, Google Cloud) including Cloud provisioning tools (e.g. More ❯

bidder, documented bids and face to face presentations. Experience of data science platforms (e.g. Databricks, Dataiku, AzureML, SageMaker) and machine learning frameworks (e.g. Keras, Tensorflow, PyTorch, scikit-learn) Cloud platforms – demonstrable experience of building and deploying solutions to Cloud (e.g. AWS, Azure, Google Cloud) including Cloud provisioning tools (e.g. More ❯

of experience in AI development. Strong understanding of machine learning, deep learning, and other AI techniques. Proficiency in Python and relevant AI libraries (e.g., TensorFlow, PyTorch). Experience with data processing and analysis tools (e.g., Pandas, SQL). Experienced with cloud platforms such as Amazon Web Services, Azure, or More ❯

and Experience Academic Background: Advanced degree in AI, statistics, mathematics, computer science, or a related field. Programming and Frameworks: Hands-on experience with Python, TensorFlow or PyTorch , and NLP libraries such as spaCy and Hugging Face. GenAI Tools: Practical experience with LangChain , Hugging Face Transformers, and embedding models for More ❯

bidder, documented bids and face to face presentations. Experience of data science platforms (e.g. Databricks, Dataiku, AzureML, SageMaker) and machine learning frameworks (e.g. Keras, Tensorflow, PyTorch, scikit-learn) Cloud platforms - demonstrable experience of building and deploying solutions to Cloud (e.g. AWS, Azure, Google Cloud) including Cloud provisioning tools (e.g. More ❯

NumPy, or Spark. At least 2 years' experience with machine learning, deep learning, or AI systems. Familiarity with key libraries and frameworks such as TensorFlow, Scikit-learn, PyTorch, Transformers, LangChain, BeautifulSoup, and OpenCV. Experience with AI APIs and platforms (e.g., OpenAI, Bedrock, Gemini, Anthropic). Knowledge of cloud infrastructure More ❯

NumPy, or Spark. At least 2 years' experience with machine learning, deep learning, or AI systems. Familiarity with key libraries and frameworks such as TensorFlow, Scikit-learn, PyTorch, Transformers, LangChain, BeautifulSoup, and OpenCV. Experience with AI APIs and platforms (e.g., OpenAI, Bedrock, Gemini, Anthropic). Knowledge of cloud infrastructure More ❯

NumPy, or Spark. At least 2 years' experience with machine learning, deep learning, or AI systems. Familiarity with key libraries and frameworks such as TensorFlow, Scikit-learn, PyTorch, Transformers, LangChain, BeautifulSoup, and OpenCV. Experience with AI APIs and platforms (e.g., OpenAI, Bedrock, Gemini, Anthropic). Knowledge of cloud infrastructure More ❯

NumPy, or Spark. At least 2 years' experience with machine learning, deep learning, or AI systems. Familiarity with key libraries and frameworks such as TensorFlow, Scikit-learn, PyTorch, Transformers, LangChain, BeautifulSoup, and OpenCV. Experience with AI APIs and platforms (e.g., OpenAI, Bedrock, Gemini, Anthropic). Knowledge of cloud infrastructure More ❯

NumPy, or Spark. At least 2 years' experience with machine learning, deep learning, or AI systems. Familiarity with key libraries and frameworks such as TensorFlow, Scikit-learn, PyTorch, Transformers, LangChain, BeautifulSoup, and OpenCV. Experience with AI APIs and platforms (e.g., OpenAI, Bedrock, Gemini, Anthropic). Knowledge of cloud infrastructure More ❯

NumPy, or Spark. At least 2 years' experience with machine learning, deep learning, or AI systems. Familiarity with key libraries and frameworks such as TensorFlow, Scikit-learn, PyTorch, Transformers, LangChain, BeautifulSoup, and OpenCV. Experience with AI APIs and platforms (e.g., OpenAI, Bedrock, Gemini, Anthropic). Knowledge of cloud infrastructure More ❯

computer systems and how they operate. Excellent Python programming skills, including experience with relevant analytical and machine learning libraries (e.g., pandas, polars, numpy, sklearn, TensorFlow/Keras, PyTorch, etc.), in addition to visualization and API libraries (matplotlib, plotly, streamlit, Flask, etc). Experience developing and implementing quantitative models from More ❯

cloud platforms like Amazon Web Services (AWS), Google Cloud Platform (GCP), and Microsoft Azure. Technical Skills - Good to have: • Expertise in any one framework (TensorFlow, Pytorch, Keras) • Experience in a statistical programming language (e.g. R or Python) and applied machine learning and AI techniques (i.e computer vision, deep learning More ❯

business problems. We prioritise clean, well-tested code with a culture of documentation and knowledge sharing. Our tech stack includes GCP, Python, GitHub, PyTorch, TensorFlow, Scikit-learn, and XGBoost. With mature infrastructure and dedicated teams for Data Engineering, Analytics, and Platform Engineering, our Data Scientists enjoy high autonomy. We More ❯

business problems. We prioritise clean, well-tested code with a culture of documentation and knowledge sharing. Our tech stack includes GCP, Python, GitHub, PyTorch, TensorFlow, Scikit-learn, and XGBoost. With mature infrastructure and dedicated teams for Data Engineering, Analytics, and Platform Engineering, our Data Scientists enjoy high autonomy. We More ❯