1 to 25 of 107 Permanent TensorFlow Jobs in the UK excluding London

science lifecycle. Expertise taking projects from ideation or experimental Jupyter notebooks to full production deployment. Strong programming skills in Python, with familiarity in ML libraries/frameworks such as TensorFlow, PyTorch, and Scikit-learn. Experience with MLOps practices including model drift detection, decay, A/B testing, integration testing, differential testing, Python package building, and code version control. Skilled 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 ❯

science. Proficiency in Python and experience with key NLP libraries and frameworks (e.g., NLTK, spaCy, Transformers, Hugging Face, BERT, Langchain). Hands-on experience with deep learning frameworks like TensorFlow or PyTorch. Strong problem-solving skills, particularly in addressing complex NLP challenges. Excellent communication and collaboration skills, with the ability to work effectively in cross-functional teams. We support More ❯

across our products. For this role, we're looking for skills across the following: Strong Python proficiency with hands-on experience in AI/ML frameworks including RAG, LangChain, TensorFlow, and PyTorch Practical experience with Generative AI and exposure to leading LLM platforms (Anthropic, Meta, Amazon , OpenAI) Proficiency with essential data science libraries including Pandas, NumPy, scikit-learn, Plotly More ❯

.NET development and AI Required Skills & Qualifications: Strong experience in C#, .NET Framework, .NET Core/6/7, ASP.NET Experience with AI/ML frameworks such as: ML.NET TensorFlow/PyTorch (for integration with .NET) Azure Cognitive Services/OpenAI/AI APIs Knowledge of RESTful APIs , microservices, and cloud platforms (Azure, AWS, or GCP) Familiarity with SQL More ❯

.NET development and AI Required Skills & Qualifications: Strong experience in C#, .NET Framework, .NET Core/6/7, ASP.NET Experience with AI/ML frameworks such as: ML.NET TensorFlow/PyTorch (for integration with .NET) Azure Cognitive Services/OpenAI/AI APIs Knowledge of RESTful APIs , microservices, and cloud platforms (Azure, AWS, or GCP) Familiarity with SQL More ❯

.NET development and AI Required Skills & Qualifications: Strong experience in C#, .NET Framework, .NET Core/6/7, ASP.NET Experience with AI/ML frameworks such as: ML.NET TensorFlow/PyTorch (for integration with .NET) Azure Cognitive Services/OpenAI/AI APIs Knowledge of RESTful APIs , microservices, and cloud platforms (Azure, AWS, or GCP) Familiarity with SQL More ❯

in professional software development Strong Python skills and a track record of delivering maintainable, well-tested code Experience with LLM APIs (OpenAI, Hugging Face, Anthropic) or ML frameworks (PyTorch, TensorFlow) Solid understanding of CI/CD, Git, testing, and agile methodologies Hands-on experience with Linux, Docker, and containerized deployments Familiarity with data engineering concepts (SQL, ETL, data lakes More ❯

technologies and machine learning algorithms, including experience in deploying and evaluating AI models. Strong proficiency in programming languages such as Python, R, and experience with libraries like Scikit-Learn, TensorFlow, or PyTorch. Experience in data manipulation, data visualization, and statistical analysis. Demonstrated ability to stay up-to-date with the latest AI advancements and integrate those insights into product More ❯

models into products. Contribute to improving infrastructure, tooling, and best practices for ML development and deployment. Skills & Experience Essential: Strong programming skills in Python (and frameworks such as PyTorch, TensorFlow, or Scikit-learn). Proven experience in developing and deploying machine learning models in production. Solid understanding of data structures, algorithms, and software engineering principles. Experience with ML pipelines More ❯

models into products. Contribute to improving infrastructure, tooling, and best practices for ML development and deployment. Skills & Experience Essential: Strong programming skills in Python (and frameworks such as PyTorch, TensorFlow, or Scikit-learn). Proven experience in developing and deploying machine learning models in production. Solid understanding of data structures, algorithms, and software engineering principles. Experience with ML pipelines More ❯

models into products. Contribute to improving infrastructure, tooling, and best practices for ML development and deployment. Skills & Experience Essential: Strong programming skills in Python (and frameworks such as PyTorch, TensorFlow, or Scikit-learn). Proven experience in developing and deploying machine learning models in production. Solid understanding of data structures, algorithms, and software engineering principles. Experience with ML pipelines More ❯

technical and non-technical stakeholders. Essential Skills & Experience Hands-on experience in ML, NLP, and GenAI (LLM/SLM). Proficiency in Python (Pandas, NumPy, Scikit-learn, PyTorch/TensorFlow). Experience with SQL/NoSQL databases, APIs, and data integration. Exposure to on-premise/open-source AI frameworks. Strong problem-solving and communication skills. Preferred Knowledge of More ❯

in AI, machine learning, and data science methodologies. Experienced Needed: Masters or PhD in a STEM subject Proficiency in Python, with experience in libraries such as pandas, scikit-learn, TensorFlow, or PyTorch. Solid SQL skills and experience working with relational databases. Exposure to cloud platforms (AWS, GCP, or Azure) would be advantageous. Strong analytical and problem-solving abilities, with More ❯

Seaborn, etc.) Knowledge of common machine learning algorithms and frameworks: linear regression, decision trees, random forests, gradient boosting (e.g., XGBoost, LightGBM), neural networks, and deep learning frameworks such as TensorFlow and PyTorch Experience building dashboards with one or more data visualization tools (experience with Metabase and/or Amplitude a plus) Preferred Technical And Professional Experience Experience with Github More ❯

Responsibilities: Research and deploy LLM-based solutions (e.g., LangChain, Mastra.ai, Pydantic) for document processing, summarization, and clinical Q&A systems. Develop and optimize predictive models using scikit-learn, PyTorch, TensorFlow, and XGBoost. Design robust data pipelines using tools like Spark and Kafka for real-time and batch processing. Manage ML lifecycle with tools such as Databricks , MLflow , and cloud More ❯

NLP, transformer models, deep learning, and scalable AI pipelines, with demonstrated involvement in LLM development, fine-tuning, or deployment. Technical Skills: Proficiency in Python and frameworks such as PyTorch , TensorFlow , or JAX . Strong familiarity with distributed computing and data engineering tools (e.g., SLURM , Apache Spark , Airflow ). Hands-on experience with LLM training, fine-tuning, and deployment (e.g. More ❯

NLP, transformer models, deep learning, and scalable AI pipelines, with demonstrated involvement in LLM development, fine-tuning, or deployment. Technical Skills: Proficiency in Python and frameworks such as PyTorch , TensorFlow , or JAX . Strong familiarity with distributed computing and data engineering tools (e.g., SLURM , Apache Spark , Airflow ). Hands-on experience with LLM training, fine-tuning, and deployment (e.g. More ❯

writing simple scripts, and building custom scenarios to prove a point. Highly Desired: Direct experience with our specific AI domain (e.g., experience with LangChain for an LLM company, or TensorFlow/PyTorch for a computer vision company). Understanding of MLOps principles and the end-to-end machine learning lifecycle. Programming/scripting experience (e.g., Python, SQL) to manipulate More ❯

writing simple scripts, and building custom scenarios to prove a point. Highly Desired: Direct experience with our specific AI domain (e.g., experience with LangChain for an LLM company, or TensorFlow/PyTorch for a computer vision company). Understanding of MLOps principles and the end-to-end machine learning lifecycle. Programming/scripting experience (e.g., Python, SQL) to manipulate More ❯

writing simple scripts, and building custom scenarios to prove a point. Highly Desired: Direct experience with our specific AI domain (e.g., experience with LangChain for an LLM company, or TensorFlow/PyTorch for a computer vision company). Understanding of MLOps principles and the end-to-end machine learning lifecycle. Programming/scripting experience (e.g., Python, SQL) to manipulate More ❯

implementing solutions defined by project leads. Desirable Experience Strong Python expertise. Experience with GNU/Linux environments. Familiarity with key data science and ML frameworks (e.g., scikit-learn, PyTorch, TensorFlow, XGBoost, Hugging Face). Experience in natural language processing, tabular data analysis, or computer vision. SQL proficiency. Exposure to containerisation (Docker, Kubernetes) and cloud-native architectures. Experience with CI More ❯

Active SC clearance(minimum 5 years UK residency required). Strong software engineering skills, with proficiency in Python. Experience across the ML lifecycle, including deploying models built in PyTorch, TensorFlow, or Scikit-learn. Hands-on cloud experience with AWS, Azure, or GCP. Knowledge of Docker and Kubernetes, with practical containerisation experience. Understanding of probability, statistics, and ML techniques. Strong More ❯