1 to 25 of 102 Permanent TensorFlow Jobs in the South East

and machine learning techniques to unstructured data, particularly with image and geometric datasets. Proficiency with data science and machine learning libraries in Python (Pandas, NumPy, Scikit-learn, PyTorch, or TensorFlow). Demonstrable experience developing and deploying complex front-end applications using the React ecosystem. Proficiency in designing, implementing, and optimising GraphQL APIs for thin-client architectures. Salary range More ❯

and machine learning techniques to unstructured data, particularly with image and geometric datasets. Proficiency with data science and machine learning libraries in Python (Pandas, NumPy, Scikit-learn, PyTorch, or TensorFlow). Demonstrable experience developing and deploying complex front-end applications using the React ecosystem. Proficiency in designing, implementing, and optimising GraphQL APIs for thin-client architectures. Salary range 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 ❯

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 ❯

We’re Looking For 2–5 years of experience in ML Engineering or MLOps. Strong proficiency in Python and experience with ML libraries/frameworks (Pandas, NumPy, Scikit-learn, TensorFlow, PyTorch). Hands-on experience implementing end-to-end ML pipelines (data ingestion, training, validation, serving). Familiarity with ML workflow orchestration tools (Airflow, Prefect, Kubeflow) and feature/ More ❯

We’re Looking For 2–5 years of experience in ML Engineering or MLOps. Strong proficiency in Python and experience with ML libraries/frameworks (Pandas, NumPy, Scikit-learn, TensorFlow, PyTorch). Hands-on experience implementing end-to-end ML pipelines (data ingestion, training, validation, serving). Familiarity with ML workflow orchestration tools (Airflow, Prefect, Kubeflow) and feature/ 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 ❯

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 ❯

to client stakeholders; conduct demos and workshops. Experience leading team of AI/software engineers Experience driving productivity and cost optimisations Skills: Python with AI/ML frameworks (PyTorch, TensorFlow). Prompt Engineering, Langchain, Langsmith/Langfuse, Gen AI/Agentic AI, Cloud platforms (Azure AI Foundry, AWS Sagemaker/Bedrock, GCP Vertex AI), MLOps/LLMOps tools (MLflow More ❯

to client stakeholders; conduct demos and workshops. Experience leading team of AI/software engineers Experience driving productivity and cost optimisations Skills: Python with AI/ML frameworks (PyTorch, TensorFlow). Prompt Engineering, Langchain, Langsmith/Langfuse, Gen AI/Agentic AI, Cloud platforms (Azure AI Foundry, AWS Sagemaker/Bedrock, GCP Vertex AI), MLOps/LLMOps tools (MLflow More ❯

to client stakeholders; conduct demos and workshops. Experience leading team of AI/software engineers Experience driving productivity and cost optimisations Skills: Python with AI/ML frameworks (PyTorch, TensorFlow). Prompt Engineering, Langchain, Langsmith/Langfuse, Gen AI/Agentic AI, Cloud platforms (Azure AI Foundry, AWS Sagemaker/Bedrock, GCP Vertex AI), MLOps/LLMOps tools (MLflow More ❯

from structured and unstructured data. Build data pipelines, models, and AI applications, using cloud platforms and frameworks such as Azure AI/ML Studio, AWS Bedrock, GCP Vertex, Spark, TensorFlow, PyTorch, etc. Build and deploy production grade fine-tuned LLMs and complex RAG architectures. Create and manage the complex and robust prompts across the GenAI solutions. Communicate effectively with More ❯

from structured and unstructured data. Build data pipelines, models, and AI applications, using cloud platforms and frameworks such as Azure AI/ML Studio, AWS Bedrock, GCP Vertex, Spark, TensorFlow, PyTorch, etc. Build and deploy production grade fine-tuned LLMs and complex RAG architectures. Create and manage the complex and robust prompts across the GenAI solutions. Communicate effectively with More ❯

from structured and unstructured data. Build data pipelines, models, and AI applications, using cloud platforms and frameworks such as Azure AI/ML Studio, AWS Bedrock, GCP Vertex, Spark, TensorFlow, PyTorch, etc. Build and deploy production grade fine-tuned LLMs and complex RAG architectures. Create and manage the complex and robust prompts across the GenAI solutions. Communicate effectively with More ❯

1. Job Title and Position Overview Title : React Native & TensorFlow Developer (Mobile AI/ML) Role Summary : We are seeking a skilled developer with expertise in React Native for mobile application development and TensorFlow for machine learning integration. The developer will be responsible for creating responsive, user-friendly mobile applications with embedded ML models to enhance functionality and … applications using React Native for both iOS and Android platforms, ensuring seamless UI and UX. Machine Learning Model Integration : Integrate and deploy machine learning models within mobile applications using TensorFlow or TensorFlow Lite. Collaboration with Data Scientists : Work closely with data scientists to understand ML requirements, assist in model selection, and optimize models for mobile deployment. Optimization and … and battery usage. Debugging and Troubleshooting : Identify, troubleshoot, and resolve app and model integration issues, maintaining smooth performance across platforms. Stay Updated : Keep up with advancements in React Native, TensorFlow, and ML to implement cutting-edge features and best practices. 3. Required Technical Skills React Native Proficiency : Strong knowledge of React Native, including components, navigation, and state management. TensorFlow More ❯

1. Job Title and Position Overview Title : React Native & TensorFlow Developer (Mobile AI/ML) Role Summary : We are seeking a skilled developer with expertise in React Native for mobile application development and TensorFlow for machine learning integration. The developer will be responsible for creating responsive, user-friendly mobile applications with embedded ML models to enhance functionality and … applications using React Native for both iOS and Android platforms, ensuring seamless UI and UX. Machine Learning Model Integration : Integrate and deploy machine learning models within mobile applications using TensorFlow or TensorFlow Lite. Collaboration with Data Scientists : Work closely with data scientists to understand ML requirements, assist in model selection, and optimize models for mobile deployment. Optimization and … and battery usage. Debugging and Troubleshooting : Identify, troubleshoot, and resolve app and model integration issues, maintaining smooth performance across platforms. Stay Updated : Keep up with advancements in React Native, TensorFlow, and ML to implement cutting-edge features and best practices. 3. Required Technical Skills React Native Proficiency : Strong knowledge of React Native, including components, navigation, and state management. TensorFlow More ❯

We’re Looking For: Proven experience in a senior-level DevOps, MLOps, or related infrastructure-focused engineering role. Strong proficiency in Python and familiarity with ML frameworks such as TensorFlow or PyTorch. Deep experience with cloud platforms (AWS, GCP, or Azure) and container orchestration tools (Docker, Kubernetes). Solid understanding of CI/CD systems (e.g., GitHub Actions, GitLab More ❯

We’re Looking For: Proven experience in a senior-level DevOps, MLOps, or related infrastructure-focused engineering role. Strong proficiency in Python and familiarity with ML frameworks such as TensorFlow or PyTorch. Deep experience with cloud platforms (AWS, GCP, or Azure) and container orchestration tools (Docker, Kubernetes). Solid understanding of CI/CD systems (e.g., GitHub Actions, GitLab More ❯

We’re Looking For: Proven experience in a senior-level DevOps, MLOps, or related infrastructure-focused engineering role. Strong proficiency in Python and familiarity with ML frameworks such as TensorFlow or PyTorch. Deep experience with cloud platforms (AWS, GCP, or Azure) and container orchestration tools (Docker, Kubernetes). Solid understanding of CI/CD systems (e.g., GitHub Actions, GitLab 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 ❯

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 ❯