51 to 75 of 315 TensorFlow Jobs in the UK

or similar - or equivalent work experience (PhD in STEM subject desirable) 2+ years experience writing production-level code for computer vision based applications with Python ML libraries, e.g Pytorch, TensorFlow Proficiency with version control and cloud computing e.g. AWS, Azure Enthusiasm for complex problem solving Strong technical communication skills, including the ability to clearly disseminate new ideas and ML More ❯

or similar - or equivalent work experience (PhD in STEM subject desirable) 2+ years experience writing production-level code for computer vision based applications with Python ML libraries, e.g Pytorch, TensorFlow Proficiency with version control and cloud computing e.g. AWS, Azure Enthusiasm for complex problem solving Strong technical communication skills, including the ability to clearly disseminate new ideas and ML More ❯

a Level 6 or Level 7 AI/ML/Data Science apprenticeship programme. Core Skills & Competencies Technical Skills Programming proficiency in Python and common ML libraries such as TensorFlow, PyTorch, or similar. Experience with Jupyter Notebooks and version control (Git/GitHub). Basic understanding of supervised/unsupervised learning, neural networks, or clustering. Analytical Abilities Ability to More ❯

Claude, Gemini, Llama, Falcon, Mistral. Model performance and optimization: Fine-tuning and optimizing LLMs for quality, latency, sustainability, and cost. Programming and NLP tools: Advanced Python, frameworks like PyTorch, TensorFlow, Hugging Face, LangChain. MLOps and deployment: Docker, Kubernetes, Azure ML Studio, MLFlow. Cloud and AI infrastructure: Experience with Azure Cloud for scalable deployment. Databases and data platforms: SQL, NoSQL More ❯

such as Python, R, C, C++, or Java, and their associated security considerations. * Previous experience with ML, LLM, deep learning and data manipulation techniques, libraries, and frameworks such as TensorFlow, PyTorch, Jax, and scikit-learn is desirable. * Experience in implementing secure coding practices, DevOps, CI/CD pipelines and familiarity with secure software development life cycle (SDLC) methodologies. * Strong More ❯

machine learning - Experience in building machine learning models for business application - Experience in applied research PREFERRED QUALIFICATIONS - Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc. - Experience with large scale distributed systems such as Hadoop, Spark etc. - PhD Amazon is an equal opportunities employer. We believe passionately that employing a diverse workforce More ❯

streaming responses and cancelable endpoints to support real-time and interactive use cases. Preferred skills and experience Machine learning experience : Familiarity with machine learning frameworks and libraries such as TensorFlow, PyTorch, or scikit-learn. Natural Language Processing (NLP) : Experience with NLP techniques and tools, such as spaCy or NLTK. Distributed systems : Knowledge of distributed systems and experience with tools More ❯

in data science or software engineering. An excellent command of the basic libraries for data science (e.g. NumPy, Pandas, Scikit-Learn) and familiarity with a deep-learning framework (e.g. TensorFlow, PyTorch, Caffe) A high level of mathematical competence and proficiency in statistics A solid grasp of essentially all of the standard data science techniques, for example, supervised/unsupervised More ❯

Python programmer in a short timeframe An excellent command of the basic libraries for data science (e.g. NumPy, Pandas, Scikit-Learn) and familiarity with a deep-learning framework (e.g. TensorFlow, PyTorch, Caffe) A high level of mathematical competence and proficiency in statistics A solid grasp of essentially all of the standard data science techniques, for example, supervised/unsupervised More ❯

Python programmer in a short timeframe An excellent command of the basic libraries for data science (e.g. NumPy, Pandas, Scikit-Learn) and familiarity with a deep-learning framework (e.g. TensorFlow, PyTorch, Caffe) A high level of mathematical competence and proficiency in statistics A solid grasp of essentially all of the standard data science techniques, for example, supervised/unsupervised More ❯

scikit-learn, etc.). Comfort working with large and complex datasets, including data wrangling and exploratory analysis. Experience (or strong interest) in GPU-powered model development (e.g. using PyTorch, TensorFlow, JAX, or similar). Demonstrated ability to work independently on real-world projects. Strong communicator, with the ability to share ideas, take feedback, and collaborate effectively. A master’s More ❯

scikit-learn, etc.). Comfort working with large and complex datasets, including data wrangling and exploratory analysis. Experience (or strong interest) in GPU-powered model development (e.g. using PyTorch, TensorFlow, JAX, or similar). Demonstrated ability to work independently on real-world projects. Strong communicator, with the ability to share ideas, take feedback, and collaborate effectively. A master’s More ❯

to write production-grade code and a good understanding of data engineering & MLOps Solid understanding of machine learning concepts, familiarity working with common frameworks such as sci-kit-learn, TensorFlow, or PyTorch Collaborative and humble great teammate with an ability to work wimulti-functionalnal teams, including technical and non-technical stakeholders Passion for learning new skills and staying up More ❯

models into production environments at scale. Expertise in Python and relevant ML libraries. Strong experience with various ML algorithms (e.g., supervised, unsupervised, reinforcement learning) and deep learning frameworks (e.g., TensorFlow, PyTorch). Experience developing generative AI applications and deploying them into production. Experience working with cloud platforms, ideally Google Cloud Platform (GCP) and BigQuery. Proficiency in working with and More ❯

and storage and to explain trade offs to customer architects. You have experience selling new technologies with a focus on product adoption and expansion. Experience with ML, deep learning, TensorFlow, Python, NLP. Expertise in sizing and designing GPU clusters (pass through vsvGPU/MIG), including storage/network throughput considerations and reference configurations for training vsinference workloads. You have More ❯

and big data engineering to productionizing classical ML and LLMs, you'll be at the core of AI infrastructure. Key Requirements: Expert in Python, ML/AI frameworks (PyTorch, TensorFlow, Hugging Face) Proven MLOps, big data, and backend/API development experience Deep understanding of NLP and LLMs Proficient with cloud platforms (AWS/GCP/Azure), Airflow, DBT More ❯

and big data engineering to productionizing classical ML and LLMs, you'll be at the core of AI infrastructure. Key Requirements: Expert in Python, ML/AI frameworks (PyTorch, TensorFlow, Hugging Face) Proven MLOps, big data, and backend/API development experience Deep understanding of NLP and LLMs Proficient with cloud platforms (AWS/GCP/Azure), Airflow, DBT More ❯

ideas need to land Bachelor's degree in computer science, Mathematics, Statistics, or related field Bonus points for Credit card or consumer finance experience Exposure to deep learning (Keras, TensorFlow) Git, Tableau, Bitbucket Master's in Data Science or similar What's on offer Up to £75k depending on experience Bonus scheme + private medical 2530 days holiday + More ❯

Computer Science, Engineering, or a related field with a strong ML focus. Solid understanding of deep learning architectures (CNNs, RNNs, Transformers). Proficiency in Python and ML libraries like TensorFlow, PyTorch, and scikit-learn. Strong experience with AWS services and cloud-native development. A proactive, collaborative mindset with a passion for learning and innovation. Bonus Points For Familiarity with More ❯

Experience with sports data is ideal but not essential. Familiarity with sports performance and biometric data analysis would be nice. Familiarity with machine learning frameworks and libraries, such as TensorFlow, PyTorch, or Scikit-learn. Any experience working with large, complex data sets and managing data pipelines, ensuring data quality and integrity. Some experience in data analysis, predictive modelling, or More ❯

Java/Python, including API integrations Knowledge of RESTful API development and integration Understanding of version control systems (e.g., Git) Specific tools include: Python Libraries like Scikit-learn or TensorFlow SQL and NoSQL databases Soft skills include: Self-starter Collaborative Fast-paced and adaptable to change Attention to detail Strong problem-solving skills Excellent communication skills Passion for software More ❯

fine-tuning Large Language Models or interactive AI applications (>1 year post-graduate experience); Technical proficiency in programming languages and frameworks commonly used in NLP and AI (e.g., Python, TensorFlow, PyTorch); Preferably several years of experience working with different AI capabilities and showcasing your passion both at work and outside work in the utilization of AI; Excellent communication skills More ❯

LLMs, with tools such as HuggingFace, Langchain, and OpenAI Extensive hands-on industry data science experience, leveraging typical machine learning and data science tools including pandas, scikit-learn, and TensorFlow/PyTorch Experience building production-grade machine learning deployments on AWS, Azure, or GCP Experience communicating and/or teaching technical concepts to non-technical and technical audiences alike More ❯

applications. Required skills: Solid foundation in AI/ML principles (e.g. neural networks, NLP, transformers, speech processing). Hands-on experience with Python and popular ML frameworks (e.g. PyTorch, TensorFlow, Hugging Face). Familiarity with LLM APIs and open-source models (e.g. GPT, Claude, Mistral, Whisper). Familiarity with agentic AI frameworks (LangChain, AutoGen, CrewAI, OpenAI Functions). Interest More ❯

to write production-grade code and a good understanding of data engineering & MLOps Solid understanding of machine learning concepts, familiarity working with common frameworks such as sci-kit-learn, TensorFlow, or PyTorch Collaborative and humble team player with an ability to work with cross-functional teams, including technical and non-technical stakeholders Passion for learning new skills and staying More ❯