1 to 25 of 179 PyTorch Jobs in London

collaboration skills Full right to work in the UK (we are unable to offer visa sponsorship for this role) Desirable (Not Essential): Familiarity with deep learning frameworks (e.g. TensorFlow, PyTorch) Exposure to cloud platforms (AWS, GCP, or Azure) Experience with experimental design, research methods, or academic publishing Understanding of MLOps, version control (Git), or containerisation (e.g. Docker) Benefits: 💰 Competitive Salary More ❯

collaboration skills Full right to work in the UK (we are unable to offer visa sponsorship for this role) Desirable (Not Essential): Familiarity with deep learning frameworks (e.g. TensorFlow, PyTorch) Exposure to cloud platforms (AWS, GCP, or Azure) Experience with experimental design, research methods, or academic publishing Understanding of MLOps, version control (Git), or containerisation (e.g. Docker) Benefits: 💰 Competitive Salary More ❯

mechanisms Conduct experiments using A/B testing and statistical analysis to validate approaches Document ML systems and provide support for ongoing performance tuning Use tools like Python, TensorFlow, PyTorch, Scikit-learn, AWS, GCP, MLflow, Docker, SQL , and others Requirements Minimum Bachelors degree in Computer Science, Machine Learning, AI, or a related field Proven experience as a Machine Learning Engineer … or in a similar role (minimum 1 year ) Strong proficiency in Python and popular ML frameworks (e.g., TensorFlow, PyTorch) Experience deploying machine learning models into production environments Solid understanding of data structures , algorithms , and statistical learning Familiarity with cloud platforms (AWS, Azure, or GCP) and ML pipeline orchestration Bonus: Experience with deep learning , NLP , recommendation systems , or computer vision Excellent More ❯

Deep understanding of AI/ML algorithms, LLMs, and modern AI architectures. • Proficiency in Python, SQL and AI/ML frameworks such as Hugging Face, LangChain, scikit-learn, TensorFlow, PyTorch and Semantic Kernel etc. • Develop compelling data visualizations and dashboards to support storytelling and real-time insights. • Ensure compliance with data governance, model explainability, and ethical AI practices, including data More ❯

data preprocessing, and feature engineering. Proven experience building and deploying RAG systems and/or LLM-powered applications in production environments. Proficiency in Python and ML libraries such as PyTorch, Hugging Face Transformers , or TensorFlow. Experience with vector search tools (e.g., FAISS, Pinecone, Weaviate) and retrieval frameworks (e.g., LangChain, LlamaIndex). Hands-on experience with fine-tuning and distillation of More ❯

software systems. Experience with microservice architecture, API development. Machine Learning (ML): Deep understanding of machine learning principles, algorithms, and techniques. Experience with popular ML frameworks and libraries like TensorFlow, PyTorch, scikit-learn, or Apache Spark. Proficiency in data preprocessing, feature engineering, and model evaluation. Knowledge of ML model deployment and serving strategies, including containerization and microservices. Familiarity with ML lifecycle … cloud platforms (e.g., AWS, Google Cloud, Azure) and containerization tools (e.g., Docker, Kubernetes). Proficiency in programming languages such as Python, experience with AI/ML frameworks (e.g., TensorFlow, PyTorch), and experience with MLOps frameworks/tools (e.g. Sagemaker pipelines, Azure ML Studio, VertexAI, Kubeflow, MLFlow, Seldon, EvidentlyAI). What we offer Culture of caring: At GlobalLogic, we prioritize a More ❯

software systems. • Experience with microservice architecture, API development. Machine Learning (ML): • Deep understanding of machine learning principles, algorithms, and techniques. • Experience with popular ML frameworks and libraries like TensorFlow, PyTorch, scikit-learn, or Apache Spark. • Proficiency in data preprocessing, feature engineering, and model evaluation. • Knowledge of ML model deployment and serving strategies, including containerization and microservices. • Familiarity with ML lifecycle … cloud platforms (e.g., AWS, Google Cloud, Azure) and containerization tools (e.g., Docker, Kubernetes). • Proficiency in programming languages such as Python, experience with AI/ML frameworks (e.g., TensorFlow, PyTorch), and experience with MLOps frameworks/tools (e.g. Sagemaker pipelines, Azure ML Studio, VertexAI, Kubeflow, MLFlow, Seldon, EvidentlyAI). What We Offer Culture of Caring: At GlobalLogic, we prioritize a More ❯

testing, monitoring, and continuous integration Requirements: 3+ years of experience in software engineering, with a focus on AI/ML integration Proficiency in Python and ML frameworks such as PyTorch or TensorFlow Strong grasp of software architecture and microservices Experience working in containerised environments (Docker, Kubernetes) Familiarity with CI/CD pipelines, secure deployment practices and cloud deployment (e.g., AWS More ❯

techniques to create solutions to challenging business problems. We prioritise clean, well-tested code with a culture of documentation and knowledge sharing. Our tech stack includes GCP, Python, GitHub, PyTorch, TensorFlow, Scikit-learn, and XGBoost. With mature infrastructure and dedicated teams for Data Engineering, Analytics, and Platform Engineering, our Data Scientists enjoy high autonomy. We tackle interesting datasets, set up More ❯

R & D problems that directly impact customers. OUR TECHNOLOGY STACK: Python • Agentic tools (Autogen, Semantic Kernel, LangChain) • SQL • MongoDB • Third-party LLM APIs • LiteLLM • MLflow • Google Cloud Platform • Docker • PyTorch • Hugging Face Transformers • SPARQL • Kubernetes WHAT YOU WILL BE DOING AT BEAMERY Join us at the forefront of transforming how organisations manage talent and plan their workforce. We're building More ❯

proficiency in programming languages for data science, e.g., SQL, R and Python alongside the ability to use tools and packages such as Alteryx, Jupyter notebook, R Markdown, TensorFlow, Keras, Pytorch etc. Practical expertise in producing reproducible code and pipelines including documentation, governance and assurance frameworks, automation and code review using tools such as Git. Skilled in data visualisation, with expertise More ❯

or a related field. Proven expertise in AI/ML fields such as LLMs, Computer Vision, Generative AI, NLP, or foundational models. Experience with deep learning frameworks (e.g., TensorFlow, PyTorch) and familiarity with cloud-based computing platforms. Strong analytical, mathematical, and coding skills (e.g., Python, C++, or Java). First author in research publications in peer-reviewed conferences or journals. More ❯

areas of machine learning at major conferences (NeurIPS, ICML, EMNLP, CVPR, etc.) and/or journals Strong high-level programming skills (e.g., Python), frameworks and tools such as DeepSpeed, Pytorch lightning, kubeflow, TensorFlow, etc. Strong written and verbal communication skills to operate in a cross functional team environment More ❯

setup of relevant pipeline and processes. Work experience with working in Linux and Microsoft Azure. Nice to Have Experience with deep learning, machine learning and NLP frameworks such as PyTorch, HuggingFace Transformer, Scikit-learn. Experience with multiple cloud platforms such as AWS, Google Cloud Platform, Oracle, NVIDIA, or on-prem environments. Perks and Benefits Salary dependent on experience Package of More ❯

AI/ML development and data science - Strong grasp of ML/AI algorithms, including LLMs and automated AI systems - Proficient in Python or R and key frameworks (TensorFlow, PyTorch, scikit-learn) - Skilled in handling large datasets, data wrangling, and statistical modelling - Comfortable working independently on end-to-end ML pipelines - Experienced in visualisation tools (e.g. Matplotlib, Seaborn, Tableau) Desirable More ❯

of industry experience or a PhD in a relevant area Strong theoretical foundation in ML, deep learning, and computer vision Proficient in Python and common ML frameworks such as PyTorch Hands-on experience with MLOps platforms and tools (experience with ClearML is beneficial) Familiarity with cloud platforms (e.g. AWS, GCP, Azure) Experience with generative AI tools (e.g. ChatGPT, GitHub Copilot More ❯

of industry experience or a PhD in a relevant area Strong theoretical foundation in ML, deep learning, and computer vision Proficient in Python and common ML frameworks such as PyTorch Hands-on experience with MLOps platforms and tools (experience with ClearML is beneficial) Familiarity with cloud platforms (e.g. AWS, GCP, Azure) Experience with generative AI tools (e.g. ChatGPT, GitHub Copilot More ❯

PREFERRED QUALIFICATIONS Masters or PhD degree in computer science, or related technical, math, or scientific field. Proven knowledge of deep learning and experience using Python and frameworks such as Pytorch, TensorFlow. Proven knowledge of Generative AI and hands-on experience building applications with large foundation models. Experiences related to AWS services such as SageMaker, EMR, S3, DynamoDB, and EC2, hands More ❯

LLMs and associated frameworks. High-growth Experience: Prior experience working in high-growth environments, ideally start-ups or scale-ups Coding Skills: Proficient in Python, SQL, and one of Pytorch, Tensorflow, Scikit-learn, with daily experience in writing, debugging, and optimising code. ML Ops Knowledge: Familiarity with tools like MLflow, Kubeflow, or Vertex AI, and experience implementing CI/CD More ❯

learning or engineering roles. Strong expertise in Machine Learning and Deep Learning, with exposure to Reinforcement Learning as a plus. Proficiency in Python and modern ML libraries (e.g., TensorFlow, PyTorch, JAX, or Keras). Experience with version control systems (GitHub, GitLab) and knowledge of clean, maintainable coding practices. Familiarity with CI/CD pipelines for automating ML workflows. Ability to More ❯

. Advanced experience with SQL for data querying and manipulation. Experience with Git, Bash, Docker, and machine learning pipelines. Experience with open-source machine learning libraries like scikit-learn, PyTorch, TensorFlow, and SciPy. Hands-on experience working with multi-modal data (images, text) and relevant ML techniques. Experience with cloud technologies and data storage solutions, including Snowflake. Understanding of personalization More ❯

techniques. To be a successful match you must have: 1+ years in a Machine Learning or ML Engineering role, with hands-on experience in deep learning frameworks (e.g., TensorFlow, PyTorch). Motivated recent graduates are encouraged to apply! A degree in Mathematics, Engineering, Statistics, Computer Science, Physics, or a related field. An advanced degree is highly preferred. Proficient in Python More ❯

ML systems in production environments, including ownership of key lifecycle stages: data collection, modeling, evaluation, deployment, and monitoring. • Proficiency in Python and modern ML and agentic frameworks such as PyTorch, TensorFlow, or LangChain, with experience packaging models into APIs or integrating them into applications. • A solid understanding of LLMs for natural language processing applications, including topics such as embeddings, prompt More ❯

learning, computer science, engineering, or a related discipline, with a BSc required and an MSc considered advantageous. Experienced in using machine learning frameworks such as Scikit-learn, Keras, and PyTorch, with additional familiarity with MLFlow and AzureML seen as a positive. Have working knowledge of CI/CD practices, ML Ops, ML pipelines, automated testing, and platforms such as AzureML More ❯

Senior Data Scientist London – Hybrid (3 days a week) £70,000 - £90,000 + Benefits Our client is a precision marketing agency, leveraging data, technology, and creativity to fuel client growth. As part of their Marketing Sciences Data Science Team More ❯