76 to 100 of 330 TensorFlow Jobs in the UK

Comfortable shipping AI features or automation products Essential skills: Strong experience with Machine Learning, LLMs, NLP and Data Science Proven track record of building and deploying AI models (Python, TensorFlow, PyTorch, LangChain) Hands-on with cloud platforms (preferably Azure, or AWS, GCP) Good understanding of APIs, microservices, and data pipelines Able to prototype quickly and communicate findings clearly Why More ❯

Comfortable shipping AI features or automation products Essential skills: Strong experience with Machine Learning, LLMs, NLP and Data Science Proven track record of building and deploying AI models (Python, TensorFlow, PyTorch, LangChain) Hands-on with cloud platforms (preferably Azure, or AWS, GCP) Good understanding of APIs, microservices, and data pipelines Able to prototype quickly and communicate findings clearly Why More ❯

mentorship and guidance. Desirable: Exposure to courses related to Artificial Intelligence, Machine Learning, or Natural Language Processing Familiarity with frameworks like Express.js, Flask, or NestJS Familiarity with libraries like TensorFlow, PyTorch, or scikit-learn Basic understanding of Amazon Web Services Culture: Coffee and snacks in the office Team socials Inclusive working environment, supporting all genders, sexualities, race, disability or More ❯

Familiarity with message brokers (Kafka, SQS/SNS, RabbitMQ). Knowledge of real-time streaming (Kafka Streams, Apache Flink, etc.). Exposure to big-data or machine-learning frameworks (TensorFlow, PyTorch, Hugging Face, LangChain). Experience with real-time streaming technologies (Kafka, Apache Storm). Understanding of infrastructure and DevOps (Terraform, Ansible, AWS, Kubernetes). Exposure to fintech or More ❯

optimising inference, managing computational resources, and ensuring reliability and maintainability. Programming & ML/LLM Frameworks Strong expertise in Python and relevant ML/LLM libraries/frameworks (e.g., PyTorch, TensorFlow, scikit-learn). Strong in Python, API design, asynchronous programming, and integration patterns. Hands-on with LangGraph/LangChain, LlamaIndex or Semantic Kernel for orchestration (tools, agents, guards, structured More ❯

Contribute to shared libraries and frameworks that support model training, evaluation, and deployment. Innovation & Research: Stay ahead of developments in GenAI (e.g. LLMs, multimodal models), ML frameworks (e.g. PyTorch, TensorFlow, Scikit-learn), orchestration tools (e.g. LangChain, LangFuse) and stay connected with AI community e.g. Hugging Face. Engineering Excellence: Apply SOLID principles, design patterns, and dependency injection to AI systems More ❯

contribute to overall project objectives. Understanding of how to use APIs to deploy machine learning models. Hands-on experience with containerization. Strong grasp of machine learning frameworks (e.g. PyTorch, Tensorflow). Knowledge of machine learning architectures, loss functions, tools and techniques. Experience developing & training machine learning models, including hyperparameter tuning and optimizing model performance. Experience with (or at least More ❯

Strong interest in Generative AI with the ability to understand and articulate key concepts. ● Experience working with LLMs, LangChain and other AI technologies. ● Familiarity with machine learning frameworks like TensorFlow or PyTorch is a bonus. — What They Offer: ● Impactful Work: Contribute to a mission-driven company revolutionising adult social care. ● Equity Opportunity: Competitive salary with equity options. ● Growth Potential More ❯

Strong interest in Generative AI with the ability to understand and articulate key concepts. ● Experience working with LLMs, LangChain and other AI technologies. ● Familiarity with machine learning frameworks like TensorFlow or PyTorch is a bonus. — What They Offer: ● Impactful Work: Contribute to a mission-driven company revolutionising adult social care. ● Equity Opportunity: Competitive salary with equity options. ● Growth Potential More ❯

automation and tooling that enhance efficiency and insight generation. Promote best practices in data governance and software design. You’ll need: Strong programming skills in Python (NumPy, Pandas, PyTorch, TensorFlow, or Scikit-learn). Experience building data pipelines and working with structured/unstructured data (SQL/NoSQL). Familiarity with the AI/ML model lifecycle from experimentation More ❯

automation and tooling that enhance efficiency and insight generation. Promote best practices in data governance and software design. You’ll need: Strong programming skills in Python (NumPy, Pandas, PyTorch, TensorFlow, or Scikit-learn). Experience building data pipelines and working with structured/unstructured data (SQL/NoSQL). Familiarity with the AI/ML model lifecycle from experimentation More ❯

Computer Science, Machine Learning or related discipline 3+ years’ experience developing ML models, with a strong focus on medical imaging Proven track record using deep learning frameworks (PyTorch/TensorFlow) Solid Python skills and familiarity with cloud or MLOps tools (Docker, Kubernetes, MLFlow) Understanding of data pipelines and image analysis techniques (segmentation, registration, feature extraction) Benefits Share options and More ❯

and risk Required Skills & Experience Production experience with Generative AI, LLMs, NLP, and RAG systems Strong knowledge of Knowledge Graphs and semantic technologies Proficient in Python, SQL, PyTorch/TensorFlow Experience with DevOps, CI/CD, DevSecOps and secure ML pipelines. Proven experience in AI/ML/Data science leadership with measurable business impact. Degree in Computer Science More ❯

and risk Required Skills & Experience Production experience with Generative AI, LLMs, NLP, and RAG systems Strong knowledge of Knowledge Graphs and semantic technologies Proficient in Python, SQL, PyTorch/TensorFlow Experience with DevOps, CI/CD, DevSecOps and secure ML pipelines. Proven experience in AI/ML/Data science leadership with measurable business impact. Degree in Computer Science More ❯

active role in open source communities. Excellent programming abilities with experience in relevant languages (Python, Rust, C++ and/or Go). Experience with relevant libraries/tools (PyTorch, Tensorflow, Neo4j) and/or AI accelerators (GPU, TPU) is a plus. Deep understanding of open source development processes (RFCs/proposals, GitHub pull requests) with demonstrable contributions to open More ❯

engineering practices. What We’re Looking For Strong academic background in Computer Science, ML, AI, or a related field. Deep hands-on experience with Python and ML frameworks (PyTorch, TensorFlow, Hugging Face). Proven background in MLOps, including model versioning, CI/CD for ML, and production monitoring. Experience building robust backend systems and APIs to serve ML models More ❯

STEM degree (Computer Science, Engineering, Data Science, or related discipline). Hands-on experience building, deploying, and managing AI/ML models and internal AI tools. Experience with Python, TensorFlow, PyTorch, cloud platforms (AWS/GCP/Azure), and data pipelines. Excellent problem-solving, analytical, and strategic thinking skills. Strong communication skills and the ability to collaborate across technical More ❯

STEM degree (Computer Science, Engineering, Data Science, or related discipline). Hands-on experience building, deploying, and managing AI/ML models and internal AI tools. Experience with Python, TensorFlow, PyTorch, cloud platforms (AWS/GCP/Azure), and data pipelines. Excellent problem-solving, analytical, and strategic thinking skills. Strong communication skills and the ability to collaborate across technical More ❯

trends. Skills & Experience: - Demonstrated hands-on experience building production AI/LLM applications. - Strong Python, API design, asynchronous programming, and integration skills. - Experience with ML/LLM frameworks (PyTorch, TensorFlow, scikit-learn, LangChain/LangGraph, LlamaIndex). - Familiarity with cloud deployment (Azure), CI/CD, Infrastructure as Code, and MLOps best practices. - Knowledge of databases, vector search, and knowledge More ❯

trends. Skills & Experience: - Demonstrated hands-on experience building production AI/LLM applications. - Strong Python, API design, asynchronous programming, and integration skills. - Experience with ML/LLM frameworks (PyTorch, TensorFlow, scikit-learn, LangChain/LangGraph, LlamaIndex). - Familiarity with cloud deployment (Azure), CI/CD, Infrastructure as Code, and MLOps best practices. - Knowledge of databases, vector search, and knowledge More ❯

the ability to work independently and as part of a multi-partner project team. Excellent communication and documentation skills. Desirable Skills Experience with AI/ML model deployment (e.g., TensorFlow, PyTorch). Experience in the design and development of front-end systems in a highly ambiguous environment. Experience in transport, logistics, or supply chain systems . Understanding of sustainability More ❯

serving. Experience managing containerised workloads (Docker, Kubernetes, Kubeflow, etc.) and integrating with CI/CD tools (Jenkins, GitHub Actions, GitLab CI). Familiarity with distributed computing frameworks (Spark, Ray, TensorFlow Distributed, PyTorch Distributed). Strong understanding of monitoring, logging, and observability for large-scale ML systems. Experience in cost optimisation for compute/GPU workloads. Excellent people leadership and More ❯

serving. Experience managing containerised workloads (Docker, Kubernetes, Kubeflow, etc.) and integrating with CI/CD tools (Jenkins, GitHub Actions, GitLab CI). Familiarity with distributed computing frameworks (Spark, Ray, TensorFlow Distributed, PyTorch Distributed). Strong understanding of monitoring, logging, and observability for large-scale ML systems. Experience in cost optimisation for compute/GPU workloads. Excellent people leadership and More ❯

serving. Experience managing containerised workloads (Docker, Kubernetes, Kubeflow, etc.) and integrating with CI/CD tools (Jenkins, GitHub Actions, GitLab CI). Familiarity with distributed computing frameworks (Spark, Ray, TensorFlow Distributed, PyTorch Distributed). Strong understanding of monitoring, logging, and observability for large-scale ML systems. Experience in cost optimisation for compute/GPU workloads. Excellent people leadership and More ❯

serving. Experience managing containerised workloads (Docker, Kubernetes, Kubeflow, etc.) and integrating with CI/CD tools (Jenkins, GitHub Actions, GitLab CI). Familiarity with distributed computing frameworks (Spark, Ray, TensorFlow Distributed, PyTorch Distributed). Strong understanding of monitoring, logging, and observability for large-scale ML systems. Experience in cost optimisation for compute/GPU workloads. Excellent people leadership and More ❯