26 to 50 of 510 TensorFlow Jobs in England

/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 ❯

to create solutions to challenging 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 tackle interesting datasets, set up 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 ❯

Any candidates with exposure to computational linguistics are highly desirable, either from a research academic or commercial perspective. Proficiency in Python and ML libraries such as Hugging Face, PyTorch, TensorFlow, and Scikit-learn. Experience deploying AI solutions into production environments using AWS/GCP/Azure. Hands-on with MLOps, CI/CD for ML, and model performance monitoring. More ❯

Requirements/Qualifications: Strong experience in Bayesian inference and probabilistic modeling : PGMs, HMMs, GPs, MCMC, variational methods, EM algorithms, etc. Proficiency in Python (must) and familiarity with PyMC, NumPyro, TensorFlow Probability , or similar probabilistic programming tools. Hands-on experience with classical ML and modern techniques, including deep learning , transformers , diffusion models , and ensemble methods . Solid understanding of feature More ❯

managing technical or data products through multiple release cycles Strong understanding of data science, machine learning concepts, and analytics capabilities Experience with AI/ML frameworks and tools (e.g., TensorFlow, PyTorch, scikit-learn, etc.) Experience with MLOps practices (e.g., model deployment, monitoring, retraining workflows) for operationalizing machine learning models effectively Excellent communication skills with the ability to translate complex More ❯

managing technical or data products through multiple release cycles Strong understanding of data science, machine learning concepts, and analytics capabilities Experience with AI/ML frameworks and tools (e.g., TensorFlow, PyTorch, scikit-learn, etc.) Experience with MLOps practices (e.g., model deployment, monitoring, retraining workflows) for operationalizing machine learning models effectively Excellent communication skills with the ability to translate complex More ❯

Rakuten Viber is one of the most popular and downloaded apps in the world. Working with us provides a unique opportunity to influence hundreds of millions of our users and to be part of the journey that makes us a More ❯

Data Scientist at PwC (Sponsorship Available) PwC is seeking a talented and forward-thinking Data Scientist to join its growing team in the UK. This is a fantastic opportunity for candidates with strong analytical expertise and programming skills, particularly in More ❯

Managing pricing and rebates shouldn't be a hassle. Enable's intelligent platform is built for the speed of today's market, eliminating disconnects between pricing strategy and rebate execution. We help companies to increase profitability and simplify the complex More ❯

Cloud Platform (GCP) AI/ML services, especially Vertex AI (Workbench, Training, Prediction, Pipelines, Feature Store). • Proficiency in Python and strong experience with AI/ML frameworks (e.g., TensorFlow, PyTorch, JAX, Hugging Face Transformers). • Experience with data engineering and building robust data pipelines for AI/ML workloads on GCP (e.g., BigQuery, Dataflow). • Solid understanding of More ❯

Cloud Platform (GCP) AI/ML services, especially Vertex AI (Workbench, Training, Prediction, Pipelines, Feature Store). • Proficiency in Python and strong experience with AI/ML frameworks (e.g., TensorFlow, PyTorch, JAX, Hugging Face Transformers). • Experience with data engineering and building robust data pipelines for AI/ML workloads on GCP (e.g., BigQuery, Dataflow). • Solid understanding of More ❯

customers, and beyond. What will make you stand out: Experience working in an analytics role in the gambling industry. Experience with CRM data analysis and customer segmentation. Knowledge of tensorflow/pytorch. Expertise in using data visualization tools such as Google Looker and working with Google's BigQuery. Experience in design and evaluation of A/B tests. Familiarity More ❯

natural language processing (NLP) techniques and developing custom solutions using large language models (LLMs) for business use cases. Proficient in Python-based AI/ML development using frameworks like TensorFlow, PyTorch, and Scikit-learn. LLM Orchestration and Development Expertise in building LLM-powered applications using frameworks such as LangChain and LangGraph, including prompt engineering, fine-tuning, and workflow orchestration. More ❯

natural language processing (NLP) techniques and developing custom solutions using large language models (LLMs) for business use cases. Proficient in Python-based AI/ML development using frameworks like TensorFlow, PyTorch, and Scikit-learn. Expertise in building LLM-powered applications using frameworks such as LangChain and LangGraph, including prompt engineering, fine-tuning, and workflow orchestration. Skilled in integrating LLMs More ❯

in AI/ML development and data science - Strong grasp of ML/AI algorithms, including LLMs and automated AI systems - Proficient in Python or R and key frameworks (TensorFlow, PyTorch, scikit-learn) - Skilled in handling large datasets, data wrangling, and statistical modelling - Comfortable working independently on end-to-end ML pipelines - Experienced in visualisation tools (e.g. Matplotlib, Seaborn More ❯

engineering. ● Proven experience in working with financial data and developing AI/ML solutions for financial services applications. ● Expertise in Python and common machine learning libraries (e.g., scikit-learn, TensorFlow, PyTorch). ● Strong understanding of data engineering principles and best practices. ● Excellent collaboration skills. ● Experience with cloud platforms such as AWS, Azure, or GCP. ● Experience with Agile development methodologies. More ❯

engineering. ● Proven experience in working with financial data and developing AI/ML solutions for financial services applications. ● Expertise in Python and common machine learning libraries (e.g., scikit-learn, TensorFlow, PyTorch). ● Strong understanding of data engineering principles and best practices. ● Excellent collaboration skills. ● Experience with cloud platforms such as AWS, Azure, or GCP. ● Experience with Agile development methodologies. More ❯

Any candidates with exposure to computational linguistics are highly desirable, either from a research academic or commercial perspective. Proficiency in Python and ML libraries such as Hugging Face, PyTorch, TensorFlow, and Scikit-learn. Experience deploying AI solutions into production environments using AWS/GCP/Azure. Hands-on with MLOps, CI/CD for ML, and model performance monitoring. More ❯

monitoring frameworks Participate in code reviews, design discussions, and performance tuning Requirements: 3+ years of experience in a Machine Learning Engineer or similar role Proficiency in Python , ML frameworks (TensorFlow, PyTorch), and deployment tools (Docker, MLflow, etc.) Experience building scalable ML pipelines in cloud environments (AWS, GCP or Azure) Familiarity with energy systems, smart metering, or IoT data is More ❯

related role, with hands-on experience in data science engineering. Proficiency in programming languages such as Python and SQL. Experience with data processing and analysis tools and technologies like TensorFlow, Keras, Scikit-learn. Strong understanding of large language models (LLMs) and machine learning (ML) algorithms and techniques. Familiarity with data visualization tools such as Power BI. Solid understanding of More ❯

financial services industry. Strong understanding of the mathematical foundations of deep learning, including multivariate calculus, linear algebra, and optimization techniques. Proficient in Python and deep learning frameworks such as TensorFlow and PyTorch. Experience with CUDA kernels and GPU profiling is a plus. Excellent communication skills, with the ability to present complex technical ideas to both technical and non-technical More ❯

financial services industry. Strong understanding of the mathematical foundations of deep learning, including multivariate calculus, linear algebra, and optimization techniques. Proficient in Python and deep learning frameworks such as TensorFlow and PyTorch. Experience with CUDA kernels and GPU profiling is a plus. Excellent communication skills, with the ability to present complex technical ideas to both technical and non-technical More ❯

software engineering concepts and best practices (e.g., versioning, testing, CI/CD, API design, MLOps) Building machine learning models and pipelines in Python, using common libraries and frameworks (e.g., TensorFlow, MLFlow) Distributed computing frameworks (e.g., Spark, Dask) Cloud platforms (e.g., AWS, Azure, GCP) and HP computing Containerization and orchestration (Docker, Kubernetes) Strong problem-solving skills and the ability to More ❯

and data-driven features into production. Your Profile: Experience in both data engineering and machine learning, with a strong portfolio of relevant projects. Proficiency in Python with libraries like TensorFlow, PyTorch, or Scikit-learn for ML, and Pandas, PySpark, or similar for data processing. Experience designing and orchestrating data pipelines with tools like Apache Airflow, Spark, or Kafka. Strong More ❯