1 to 25 of 58 TensorFlow Jobs in the Midlands

Bachelor’s or Master’s degree in Computer Science, Engineering, Mathematics, Physics, or a related field. Strong programming skills in Python. Experience with machine learning frameworks such as PyTorch, TensorFlow, or Scikit-learn. Proficiency in data manipulation and analysis using tools such as Polars, Pandas, NumPy, or SQL. Solid understanding of algorithms, statistics, and data structures. Experience with cloud More ❯

workflows, models, and system architecture for transparency and reproducibility Requirements Proficiency in programming languages such as Python, Java, or C++ Strong understanding of machine learning frameworks (e.g., PyTorch (preferred), TensorFlow, Scikit-learn) Experience with data processing tools and cloud platforms (e.g., Azure, GCP, AWS) Knowledge of deep learning, NLP, and computer vision techniques, (especially in the context of Microsoft More ❯

and presentations. This role is for you if: Python for API and Model development (Machine learning frameworks and tooling e.g. Sklearn) and (Deep learning frameworks such as Pytorch and Tensorflow). Understanding of machine learning techniques. Experience with data manipulation libraries (e.g. Pandas, Spark, SQL). Git for version control. Cloud experience (we use Azure/GCP/AWS More ❯

/RFP process, as preferred 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. Terraform). Technology deployment- proven More ❯

solution direction, Contribute to internal best practices and the technical growth of the team. Required Qualifications Proficiency in Python and experience with machine learning libraries (e.g. scikit-learn, PyTorch, TensorFlow), Proven ability to deliver data science projects with measurable outcomes, Strong grounding in statistics, modelling, or applied mathematics, Experience with real-world data: cleaning, preprocessing, feature engineering, and evaluation More ❯

models. Proficiency in programming languages such as Python, R, or MATLAB. Experience with data wrangling, feature engineering, and preparing datasets for model validation. Familiarity with machine learning frameworks (e.g., TensorFlow, PyTorch, Scikit-learn) and model evaluation techniques. Experience with cloud platforms (e.g., AWS, Azure, GCP) and deployment of models in cloud environments. Experience with data visualization tools such as More ❯

and monitoring (e.g. Kubeflow) - Expert knowledge of automated artefact deployment using YAML based CI/CD pipelines and Terraform - Working knowledge of one or more ML engineering frameworks (e.g. TensorFlow, PyTorch, Keras, Scikit-Learn) - Working knowledge of object-oriented programming and unit testing in Python - Working knowledge of application and information security principles and practices (e.g. OWASP for Machine More ❯

and monitoring (e.g. Kubeflow) - Expert knowledge of automated artefact deployment using YAML based CI/CD pipelines and Terraform - Working knowledge of one or more ML engineering frameworks (e.g. TensorFlow, PyTorch, Keras, Scikit-Learn) - Working knowledge of object-oriented programming and unit testing in Python - Working knowledge of application and information security principles and practices (e.g. OWASP for Machine More ❯

and monitoring (e.g. Kubeflow) - Expert knowledge of automated artefact deployment using YAML based CI/CD pipelines and Terraform - Working knowledge of one or more ML engineering frameworks (e.g. TensorFlow, PyTorch, Keras, Scikit-Learn) - Working knowledge of object-oriented programming and unit testing in Python - Working knowledge of application and information security principles and practices (e.g. OWASP for Machine More ❯

and monitoring (e.g. Kubeflow) - Expert knowledge of automated artefact deployment using YAML based CI/CD pipelines and Terraform - Working knowledge of one or more ML engineering frameworks (e.g. TensorFlow, PyTorch, Keras, Scikit-Learn) - Working knowledge of object-oriented programming and unit testing in Python - Working knowledge of application and information security principles and practices (e.g. OWASP for Machine More ❯

and monitoring (e.g. Kubeflow) - Expert knowledge of automated artefact deployment using YAML based CI/CD pipelines and Terraform - Working knowledge of one or more ML engineering frameworks (e.g. TensorFlow, PyTorch, Keras, Scikit-Learn) - Working knowledge of object-oriented programming and unit testing in Python - Working knowledge of application and information security principles and practices (e.g. OWASP for Machine More ❯

and monitoring (e.g. Kubeflow) - Expert knowledge of automated artefact deployment using YAML based CI/CD pipelines and Terraform - Working knowledge of one or more ML engineering frameworks (e.g. TensorFlow, PyTorch, Keras, Scikit-Learn) - Working knowledge of object-oriented programming and unit testing in Python - Working knowledge of application and information security principles and practices (e.g. OWASP for Machine More ❯

Strong knowledge of statistical techniques and validation methodologies. Proficiency in Python, R, or MATLAB. Experience with data wrangling, feature engineering, and dataset preparation. Knowledge of machine learning frameworks like TensorFlow, PyTorch, Scikit-learn. Experience with cloud platforms (AWS, Azure, GCP) and deploying models. Ability to use data visualization tools like Tableau or Power BI. Nice-to-Have: Familiarity with More ❯

are looking for: Essential: UK SC Clearance or the ability obtain it Demonstrable experience developing a variety of machine learning models Strong grasp of machine learning frameworks (e.g. PyTorch, Tensorflow) Knowledge of machine learning architectures, loss functions, tools and techniques Experience training machine learning models, including hyperparameter tuning and optimizing model performance Experience with (or at least exposure to More ❯

Data Scientist 's working across a variety of companies & industries Provide hands-on coding sessions and real-world project mentorship using Python and relevant ML libraries (e.g., Scikit-learn, TensorFlow, PyTorch etc) Incorporate cloud-based tools and services (e.g., AWS, GCP, or Azure) into training to simulate modern ML engineering environments (Cloud Training can be provided to you) Keep More ❯

Data Scientist 's working across a variety of companies & industries Provide hands-on coding sessions and real-world project mentorship using Python and relevant ML libraries (e.g., Scikit-learn, TensorFlow, PyTorch etc) Incorporate cloud-based tools and services (e.g., AWS, GCP, or Azure) into training to simulate modern ML engineering environments (Cloud Training can be provided to you) Keep More ❯

Data Scientist 's working across a variety of companies & industries Provide hands-on coding sessions and real-world project mentorship using Python and relevant ML libraries (e.g., Scikit-learn, TensorFlow, PyTorch etc) Incorporate cloud-based tools and services (e.g., AWS, GCP, or Azure) into training to simulate modern ML engineering environments (Cloud Training can be provided to you) Keep More ❯

Data Scientist 's working across a variety of companies & industries Provide hands-on coding sessions and real-world project mentorship using Python and relevant ML libraries (e.g., Scikit-learn, TensorFlow, PyTorch etc) Incorporate cloud-based tools and services (e.g., AWS, GCP, or Azure) into training to simulate modern ML engineering environments (Cloud Training can be provided to you) Keep More ❯

Data Scientist 's working across a variety of companies & industries Provide hands-on coding sessions and real-world project mentorship using Python and relevant ML libraries (e.g., Scikit-learn, TensorFlow, PyTorch etc) Incorporate cloud-based tools and services (e.g., AWS, GCP, or Azure) into training to simulate modern ML engineering environments (Cloud Training can be provided to you) Keep More ❯

Data Scientist 's working across a variety of companies & industries Provide hands-on coding sessions and real-world project mentorship using Python and relevant ML libraries (e.g., Scikit-learn, TensorFlow, PyTorch etc) Incorporate cloud-based tools and services (e.g., AWS, GCP, or Azure) into training to simulate modern ML engineering environments (Cloud Training can be provided to you) Keep More ❯

Data Scientist 's working across a variety of companies & industries Provide hands-on coding sessions and real-world project mentorship using Python and relevant ML libraries (e.g., Scikit-learn, TensorFlow, PyTorch etc) Incorporate cloud-based tools and services (e.g., AWS, GCP, or Azure) into training to simulate modern ML engineering environments (Cloud Training can be provided to you) Keep More ❯

Data Scientist 's working across a variety of companies & industries Provide hands-on coding sessions and real-world project mentorship using Python and relevant ML libraries (e.g., Scikit-learn, TensorFlow, PyTorch etc) Incorporate cloud-based tools and services (e.g., AWS, GCP, or Azure) into training to simulate modern ML engineering environments (Cloud Training can be provided to you) Keep More ❯

Data Scientist 's working across a variety of companies & industries Provide hands-on coding sessions and real-world project mentorship using Python and relevant ML libraries (e.g., Scikit-learn, TensorFlow, PyTorch etc) Incorporate cloud-based tools and services (e.g., AWS, GCP, or Azure) into training to simulate modern ML engineering environments (Cloud Training can be provided to you) Keep More ❯

Data Scientist 's working across a variety of companies & industries Provide hands-on coding sessions and real-world project mentorship using Python and relevant ML libraries (e.g., Scikit-learn, TensorFlow, PyTorch etc) Incorporate cloud-based tools and services (e.g., AWS, GCP, or Azure) into training to simulate modern ML engineering environments (Cloud Training can be provided to you) Keep More ❯

Data Scientist 's working across a variety of companies & industries Provide hands-on coding sessions and real-world project mentorship using Python and relevant ML libraries (e.g., Scikit-learn, TensorFlow, PyTorch etc) Incorporate cloud-based tools and services (e.g., AWS, GCP, or Azure) into training to simulate modern ML engineering environments (Cloud Training can be provided to you) Keep More ❯