1 to 25 of 106 Permanent PyTorch Jobs in the UK

lifecycle. Expertise taking projects from ideation or experimental Jupyter notebooks to full production deployment. Strong programming skills in Python, with familiarity in ML libraries/frameworks such as TensorFlow, PyTorch, and Scikit-learn. Experience with MLOps practices including model drift detection, decay, A/B testing, integration testing, differential testing, Python package building, and code version control. Skilled in data More ❯

platform scale. Proven track record of leading ML engineering projects from architecture to deployment, including ownership of production-grade systems. Deep expertise in ML frameworks and engineering stacks (TensorFlow, PyTorch, JAX, Ray, MLflow, Kubeflow). Proficiency in Python and at least one backend language (e.g., Java, Scala, Go, C++). Strong understanding of cloud ML infrastructure (AWS SageMaker, GCP Vertex More ❯

asyncio for concurrent processing, and building robust automation scripts with proper logging, testing (pytest), and documentation. AI & Machine Learning Frameworks - Deep expertise in AI/ML frameworks including TensorFlow, PyTorch, Scikit-learn, and Hugging Face Transformers. Experience building, training, and deploying machine learning models for classification, regression, clustering, and NLP tasks. Understanding of model evaluation metrics, hyperparameter tuning, feature engineering More ❯

Experience with predictive modeling techniques such as regression, classification, clustering, or time-series forecasting. Proficiency in Python and experience with data science libraries (e.g., Pandas, NumPy, scikit-learn, XGBoost, PyTorch, TensorFlow). Strong experience with SQL and data manipulation across large datasets. Familiarity with data visualization tools (e.g., Matplotlib, Seaborn, Plotly, Tableau, or Power BI). Exposure to modern collaborative More ❯

Master's degree in Computer Science, Artificial Intelligence, Data Science, or a related field (or equivalent experience). Technical Skills: Proficiency in Python and deep learning frameworks (e.g., TensorFlow, PyTorch). Strong understanding of NLP techniques, including tokenization, embeddings, transformers, and attention mechanisms. Experience in retraining and fine-tuning LLMs using large-scale datasets. Familiarity with cloud platforms like AWS More ❯

knowledge and familiarity with cloud platforms like Amazon Web Services (AWS), Google Cloud Platform (GCP), and Microsoft Azure. Technical Skills – Good to have: • Expertise in any one framework (TensorFlow, Pytorch, Keras) • Experience in a statistical programming language (e.g. R or Python) and applied machine learning and AI techniques (i.e computer vision, deep learning, conversational AI, and natural language processing frameworks. More ❯

to get bootstrapped quickly is a must. Core AI & Machine Learning Python Vertex AI/Hugging Face LangChain/BAML — LLM frameworks Langfuse, LangSmith — Observability Pandas, NumPy, scikit-learn, PyTorch — Data & ML stack Data & Infrastructure BigQuery — Cloud data warehouse PostgreSQL — Application data Pulumi — Infrastructure as Code (TypeScript) Google Cloud Platform (GCP) — Cloud provider GitHub Actions — CI/CD Docker/ More ❯

familiarity with 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 More ❯

familiarity with 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 More ❯

Statistics, Mathematics, Physics, Computer Science, Machine Learning) Strong programming skills in Python (production-level) and SQL; confident with modern ML/AI libraries such as scikit-learn, TensorFlow, or PyTorch Familiarity with MLOps frameworks, model deployment, and cloud-based platforms (Databricks, AWS, Azure) Strong experience with data visualisation tools and techniques; able to turn complex results into accessible insights Excellent More ❯

FastAPI). Data Science: Familiarity or experience with classical NLP techniques (BERT, topic modelling, summarisation), statistical analysis, and knowledge graphs. Deep Learning: Familiarity or experience with Deep Learning (TensorFlow, PyTorch). Benefits Package and Benefits: Competitive Salary Bonus Scheme Private Healthcare Insurance 25 Days Annual Leave + Bank Holidays Up to 10 days allocated for development training per year Enhanced More ❯

of-concept , model monitoring , and adoption of emerging AI tech. What We’re Looking For 5+ years in data engineering, with team or project leadership experience. Advanced Python (Pandas, PyTorch, TensorFlow, Scikit-learn). Strong AWS/GCP , MySQL , and CI/CD experience; Docker/Kubernetes a plus. Excellent communication, organisation, and problem-solving skills. Passion for innovation and More ❯

algorithms, primarily for speech and audio applications. Develop and execute evaluation pipelines to test models on prototype and production systems. Debug and optimise ML workflows and code using Python, PyTorch/TensorFlow, and related tools. Collaborate with software and hardware teams to integrate AI solutions seamlessly into devices. Maintain comprehensive technical documentation for models, algorithms, and workflows. Support internal teams More ❯

modelling, or personalization/recommendation. Familiarity with state-of-the-art practice in these domains Proficient in Python, and experience with machine learning and deep learning toolkits (e.g., TensorFlow, PyTorch, NumPy, Scikit-Learn, Pandas) Scientific thinking, ability to design experiments and training frameworks, and to outline and evaluate intrinsic and extrinsic metrics for model performance aligned with business goals Solid More ❯

Requirements Extensive experience with version control tools, preferably Git. Proficiency in Docker and container orchestration. Advanced proficiency in Python and familiarity with AI and machine learning libraries (e.g., TensorFlow, PyTorch, Scikit-learn). Strong understanding of algorithms, data structures, and software engineering principles. Experience in deploying AI models in a production environment. Proven ability to collaborate effectively with cross-functional More ❯

in Python Knowledge of machine learning, deep learning, natural language processing, computer vision and other AI techniques and algorithms Experience in developing and deploying AI solutions using Python, TensorFlow, PyTorch, Keras, Snowflake, or similar frameworks and tools Experience developing REST-based APIs Knowledge and some experience with DevOps and CI/CD tools (such as Jenkins, Ansible, Packer, Docker) Exposure More ❯

AI/ML engineering role, with a demonstrable track record of building and shipping complex systems. Expert-level proficiency in Python and its core AI/ML libraries (e.g., PyTorch, TensorFlow, LangChain, LlamaIndex), and comfortable transitioning to a 'pilot' role using AI tools to amplify your productivity. Proven experience designing, deploying, and managing scalable AI solutions on at least one More ❯

Deep understanding of machine learning algorithms, optimization, architectures, and evaluation. Experience with data engineering workflows, including ETL, pipeline design, and feature extraction. Proficiency in Python and libraries such as PyTorch, TensorFlow, scikit-learn, Hugging Face, LangChain, and OpenAI/Anthropic APIs. Familiarity with DevOps & tooling (Git, CI/CD, API integration), front-end & visualization (Streamlit, Gradio, React), and cloud environments More ❯

and unsupervised learning, natural language processing, Bayesian statistics, time-series forecasting, collaborative filtering etc) ? Proficiency in Python with familiarity to ML libraries e.g. pandas, numpy, scipy, scikit-learn, tensorflow, pytorch) ? Familiarity with cloud platforms (GCP, AWS, Azure) and tools like Dataiku, Databricks. ? Experience with ML Ops, including model deployment, monitoring, and retraining pipelines. ? Ability to work cross-functionally with marketing More ❯

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 this role More ❯

reviews, architectural decision-making, and technical debt management Ability to establish coding standards and best practices across teams AI/ML Expertise Strong understanding of machine learning frameworks (TensorFlow, PyTorch, Scikit-learn) Experience with LLM integration (OpenAI, Anthropic, open-source models) Knowledge of RAG architectures, prompt engineering, and vector databases (Pinecone, Weaviate) Experience with MLOps tools and monitoring model performance More ❯

with a strong focus on AI and machine learning. Solid understanding of machine learning algorithms, data structures, and statistical modelling. Experience with AI frameworks and libraries such as TensorFlow, PyTorch, or Scikit-learn. Strong programming skills in languages such as Python, Java, or Scala. Strong experience with cloud-based AI services and platforms (e.g., AWS, Azure, GCP, ServiceNow, SalesForce). More ❯

including 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 ❯

support in healthcare. What they’re looking for Solid programming skills in Python or JavaScript (Node.js) . A good grasp of RESTful APIs . Experience with Hugging Face, LangChain, PyTorch , or similar AI/ML tools. Familiarity with CI/CD practices. A degree in Computer Science, Informatics , or similar. 3+ years building and optimizing backend systems for high-performance More ❯

orchestration. Experience mentoring other engineers and leading by example. Strong understanding of software architecture principles and system design. Familiarity with integrating AI/ML APIs or frameworks (e.g., TensorFlow, PyTorch) is a plus. Excellent communication skills and a collaborative approach to problem solving. The Mindset We Value: Relentless Innovation: We're looking for individuals who are constantly exploring the edges More ❯