1 to 25 of 221 PyTorch Jobs in the UK excluding London

algorithms, statistical methods, and predictive modeling Experience with NLP techniques for text analysis, classification, and information extraction Knowledge of deep learning frameworks such as PyTorch or TensorFlow Experience with data visualization tools (Matplotlib, Seaborn, Plotly, or similar) Strong analytical mindset with a focus on solving real-world problems Excellent communication More ❯

and neural networks. Strong programming skills in languages such as Python, R, or Java Familiarity with AI libraries, frameworks, and tools such as TensorFlow, PyTorch, or Keras. Proven understanding of cloud computing platforms (e.g., AWS, Azure, Google Cloud) and experience deploying AI models on these platforms. Solid understanding of AI More ❯

environment, MLOps and model integration into larger scale applications. Experience with Machine and Deep Learning libraries such as Scikit-learn, XGBoost, MXNet, TensorFlow or PyTorch Exposition to GenAI and solid understanding of multimodal AI via HuggingFace, Llama, VertexAI, AWS Bedrock or GPT Knowledge of data pipeline and workflow management tools More ❯

computer science, Software Engineering, or a related field. Proficiency in programming languages (e.g., Python, C#, C++). Experience with deep learning frameworks (e.g., TensorFlow, PyTorch). Knowledge of cloud platforms (e.g., Azure). Familiarity with containerization is a plus (e.g., Docker, Kubernetes). Knowledge of big data technologies (e.g., Hadoop More ❯

Requirements: Bachelor’s, Master’s, or PhD in Computer Science, Data Science, Bioinformatics, or related field. Proficiency in Python and ML frameworks (e.g., TensorFlow, PyTorch). Experience with bioinformatics tools (e.g., Biopython, RDKit). Strong knowledge of statistical models, deep learning, and data preprocessing. Familiarity with cloud platforms (AWS, GCP More ❯

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 More ❯

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 More ❯

years of hands-on experience in AI and machine learning. Technical Expertise: Strong proficiency in Python. Expertise in machine learning frameworks such as TensorFlow, PyTorch, Keras, or similar. Machine Learning: Solid understanding of supervised and unsupervised learning, deep learning (CNNs, RNNs, GANs), and reinforcement learning. Data Handling: Proficient in data More ❯

learning, probabilistic modeling, and/or NLP. Proficiency in programming languages such as Python, R, or Julia, with experience using ML frameworks (e.g., TensorFlow, PyTorch, Scikit-learn). Familiarity with biological datasets such as genomic, transcriptomic, proteomic, or imaging data. Experience working with large-scale datasets and cloud computing platforms More ❯

will bring: Essential: 5+ years of experience in data science, machine learning, or AI innovation. Strong coding skills in Python (e.g., Pandas, NumPy, TensorFlow, PyTorch) and SQL. Proven experience deploying ML models in production environments. 3+ years in a leadership or mentorship role within AI or data teams. Clear communicator More ❯

DevOps, or ML Engineering roles Proven expertise deploying and scaling Generative AI models (GPT, Stable Diffusion, BERT) Proficiency with Python and ML frameworks (TensorFlow, PyTorch, Hugging Face) Strong cloud platform experience (AWS, GCP, Azure) and managed AI/ML services Practical experience with Docker, Kubernetes, and container orchestration Databricks expertise More ❯

Azure). Stay up-to-date with the latest research and advancements in AI, Image processing, and Computer Vision. Familiarity with deep learning frameworks (PyTorch, TensorFlow) including OpenCV. Strong communication and analytical skills. Ability to work in teams in a diverse, multi-stakeholder environment comprising of Business and Technology teams. More ❯

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 More ❯

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 More ❯

CD) automation, rigorous code reviews, documentation as communication. Preferred Qualifications Familiar with data manipulation and experience with Python libraries like Flask, FastAPI, Pandas, PySpark, PyTorch, to name a few. Proficiency in statistics and/or machine learning libraries like NumPy, matplotlib, seaborn, scikit-learn, etc. Experience in building ETL/ More ❯

to fine-tune those models eg. XGBoost, Deep Neural Networks, Transformers, Markov chains, etc. Experience using specialized machine learning libraries e.g. Fastai, Keras, Tensorflow, pytorch, sci-kit learn, huggingface, etc. Must demonstrate the capacity of reading, understanding and implementing new techniques in the field of machine learning as they emerge. More ❯

as fraud prevention or credit scoring. Machine Learning Expertise: Strong understanding of machine learning algorithms and their practical applications. Experience with frameworks like TensorFlow, PyTorch, and scikit-learn. Data Engineering: Proficiency in developing and maintaining real-time data pipelines. Experience with ETL processes, Python, and SQL. Familiarity with big data More ❯

a deep understanding of machine learning algorithms, deep learning, and generative models. Advanced AI Skills and Testing: Familiarity with deep learning frameworks (e.g., TensorFlow, PyTorch), hands-on experience in deploying AI/ML solutions as a service/REST API on Cloud or Kubernetes, and proficiency in testing of developed More ❯

workloads. Strong proficiency with Docker, Kubernetes, and infrastructure automation (Terraform, CloudFormation). Solid programming skills in Python and familiarity with ML frameworks like TensorFlow, PyTorch . Experience designing CI/CD pipelines for ML workflows and deployment automation. Exposure to LLM Ops , including managing fine-tuning and deployment of large More ❯

engineering knowledge, including data structures, algorithms, system design, and OOP. You have advanced knowledge of LLM architectures and ML/DL frameworks (e.g. TensorFlow, PyTorch, LangChain, Keras, scikit-learn). You're ready to design, deploy and maintain production-grade Machine Learning systems. You're willing to champion best practices More ❯

to explain complex ideas simply, and work well in cross-functional teams Tech You'll Work With ML & Data Science Python (primary language) TensorFlow, PyTorch, or Keras NumPy, pandas Data pipelines (Azure Data Factory, Airflow, etc.) Applied ML: NLP, CV, transformers, GANs, time series, etc. Engineering & Cloud Azure (or similar More ❯

CE, ML or related field research - Experience programming in Java, C++, Python or related language - 3+ years' experience with modeling languages and tools like PyTorch/TensorFlow, R, scikit-learn, numpy, scipy, etc - Solid ML background and familiar with standard NLU, NLG, and LLM techniques PREFERRED QUALIFICATIONS - PhD in Computer More ❯

SageMaker, ECS) and cloud infrastructure management Programming and ML Frameworks: Proficiency in Python and experience with ML frameworks such as scikit-learn, TensorFlow, or PyTorch CI/CD Experience: Experience with CI/CD tools and practices (e.g., GitHub Actions, Jenkins) and the ability to design and implement efficient CI More ❯

software solutions. Expertise in at least one relevant programming language (e.g., Python, Java, or C++) Familiarity with at least one AI framework (e.g., TensorFlow, PyTorch, or Scikit-learn). Knowledge of AI algorithms, machine learning techniques, and data analytics methodologies, with an emphasis on engineering applications. Understanding of data preprocessing More ❯

to fine-tune those models eg. XGBoost, Deep Neural Networks, Transformers, Markov chains, etc. Experience using specialized machine learning libraries e.g. Fastai, Keras, Tensorflow, pytorch, sci-kit learn, huggingface, etc. Must demonstrate the capacity of reading, understanding and implementing new techniques in the field of machine learning as they emerge. More ❯