1 to 25 of 345 Permanent PyTorch Jobs in London

Machine Learning Deep Learning Neural Networks Natural Language Processing (NLP) Generative AI Large Language Models (LLMs) Retrieval-Augmented Generation (RAG) Reinforcement Learning Frameworks & Technologies PyTorch TensorFlow Scikit-learn LangChain Hugging Face OpenAI and Azure OpenAI Services Vector Databases Docker Kubernetes Cloud Platforms Microsoft Azure Azure AI Services Azure Machine Learning ...

quality assessment. Good foundation in statistics, probability, optimization, experimentation, and applied machine learning. Advanced proficiency in Python and modern AI frameworks, including PyTorch, TensorFlow, Scikit‐Learn, Hugging Face, LangChain, Semantic Kernel, and related ecosystems. Experience building and scaling enterprise AI platforms, ML infrastructure, and intelligent applications serving thousands of users. ...

Learning, predictive modelling and applied AI, developing, evaluating and operationalising models using state-of-the-art libraries and frameworks such as scikit-learn, TensorFlow, PyTorch and XGBoost, helping tackle complex challenges including fraud prevention, credit risk management and customer personalisation. Generative AI, Large Language Models and autonomous agent systems, building ...

Skills & Experience: Experience in machine learning, data science, or applied AI roles. Proficiency in Python and ML libraries (Pandas, NumPy, Scikit-learn, TensorFlow, PyTorch). Strong understanding of statistics, ML algorithms, and model evaluation techniques. Experience working with cloud platforms (AWS, Azure, or GCP) and ML pipelines. Ability to analyse ...

Skills & Experience: Experience in machine learning, data science, or applied AI roles. Proficiency in Python and ML libraries (Pandas, NumPy, Scikit-learn, TensorFlow, PyTorch). Strong understanding of statistics, ML algorithms, and model evaluation techniques. Experience working with cloud platforms (AWS, Azure, or GCP) and ML pipelines. Ability to analyse ...

lifecycle expertise: feature engineering, model training, evaluation and production deployment, including MLOps, monitoring and drift detection. Practical knowledge of ML frameworks (e.g. scikit‐learn, PyTorch, XGBoost) and cloud‐native ML services (SageMaker, Azure ML, Vertex AI). Architecture and delivery of scalable cloud data and AI platforms on AWS, Azure ...

parallel and high-throughput file systems (e.g. Everpure, WEKA, VAST, NetApp) sized for training and checkpointing workloads. AI Software, MLOps & Generative AI ML frameworks: PyTorch and TensorFlow at a working, hands-on level. Distributed training: Horovod, DeepSpeed, Megatron-LM, or equivalent multi-node training frameworks. Inference & serving: NVIDIA Triton, vLLM ...

bring 5+ years of experience in AI, Machine Learning, Data Science, or related fields. Strong Python skills and experience with frameworks such as PyTorch, TensorFlow, and Hugging Face. Experience taking AI proof-of-concepts from idea to production. Strong knowledge of deep learning, NLP, and LLM architectures and experience ...

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 ...

experience with classical NLP techniques (BERT, topic modelling, summarisation), statistical analysis, and knowledge graphs. Deep Learning: Familiarity or experience with Deep Learning (TensorFlow, PyTorch). What We Offer: Competitive Salary Bonus Scheme Private Healthcare Insurance 25 Days Annual Leave + Bank Holidays Up to 10 days allocated for development training ...

Machine Learning Deep Learning Neural Networks Natural Language Processing (NLP) Generative AI Large Language Models (LLMs) Retrieval-Augmented Generation (RAG) Reinforcement Learning Frameworks & Technologies PyTorch TensorFlow #J-18808-Ljbffr ...

concept through to production. Strong technical knowledge, including proficiency in Python and experience with core data science and ML libraries (e.g., scikit-learn, pandas, PyTorch or TensorFlow). Practical experience with Databricks, including MLflow for experiment tracking and model management, and Spark-based data processing. Familiarity with Generative AI concepts ...

Science, Data Science, Machine Learning, or related field. Experience building and deploying agentic AI applications in production environments. Expertise with ML frameworks such as PyTorch, TensorFlow, and scikit‐learn. Proficiency in Python; experience writing comprehensive tests and building evaluation harnesses for agents and prompts. Hands‐on experience with agent frameworks ...

with a track record of building and maintaining production‐quality systems. Expert‐level Python experience with numerical, statistical, or ML libraries (e.g. NumPy, pandas, PyTorch, JAX, TensorFlow). Deep understanding of statistical modelling, optimisation, or machine‐learning techniques. Experience building and operating backend systems and data pipelines in a cloud ...

token classification. Working knowledge of large language models, including prompting and retrieval-augmented generation (RAG). Experience or coursework in Deep Learning frameworks like PyTorch or TensorFlow. Strong problem‐solving skills and a curiosity for learning new technologies. Good verbal and written communication skills. Familiarity with cloud platforms (e.g., Azure ...

Track record of leading ML/AI technical initiatives across multiple teams Strong experience with cloud platforms (AWS, Azure, GCP) Experience with ML frameworks (PyTorch, TensorFlow, scikit-learn) and Gen AI/Agentic frameworks (LangGraph, LangChain, VectorDBs, RAG) Understanding of responsible AI practices, including guardrails, hallucination mitigation, and output quality ...

generate actionable insights that inform business and product decisions Desirable: Hands-on coding and prototyping experience in AI/ML development (Python, TensorFlow, PyTorch) Experience with proof-of-concept development and technical validation of new AI technologies Background in data science or machine learning engineering with an understanding of model ...

LLMs, NLP, or computer vision projects Knowledge of AWS, Azure, or GCP Familiarity with Docker, APIs, or Git workflowsFamiliarity with frameworks such as PyTorch, TensorFlow, or Scikit-learn Internship, university project, or personal portfolio related to AI/ML What’s on Offer Competitive graduate salary package Company stock options ...

experience training, deploying, and maintaining machine learning models in production environments Proficiency in Python and relevant AI/ML libraries (e.g. scikit‐learn, TensorFlow, PyTorch) Experience with MLOps practices and tools for managing the machine learning lifecycle Experience building and deploying Generative AI applications, including familiarity with LLMOps Exposure ...

Broad knowledge of MLOps tooling – for versioning, reproducibility, observability etc. Experience monitoring, maintaining, enhancing existing models over an extended time period Extensive experience with pytorch and related data science python libraries (e.g. pandas) Experience of containerising applications or models for deployment (Docker) Experience with one of the major public cloud ...

with a track record of building and maintaining production‐quality systems. Expert‐level Python experience with numerical, statistical, or ML libraries (e.g. NumPy, pandas, PyTorch, JAX, TensorFlow). Deep understanding of statistical modelling, optimisation, or machine‐learning techniques. Experience building and operating backend systems and data pipelines in a cloud ...

measurement/validation discipline Strong Python and SQL; comfortable with large transactional datasets and common DS/ML libraries (e.g. pandas, scikit-learn, XGBoost, PyTorch or similar) Experience collaborating on MLOps-style workflows (experiment tracking, serving, monitoring) and shipping with engineers Able to communicate uncertainty and model limitations clearly ...

Platform, or Microsoft Azure) Knowledge of containerisation technologies like Docker and orchestration tools such as Kubernetes Experience with AI/ML frameworks (e.g., TensorFlow, PyTorch, or Java-based ML libraries) Strong problem-solving and communication skills Preferred Qualifications Experience with NLP, computer vision, or recommendation systems Familiarity with MLOps practices ...

measurement/validation discipline Strong Python and SQL; comfortable with large transactional datasets and common DS/ML libraries (e.g. pandas, scikit‐learn, XGBoost, PyTorch or similar) Experience collaborating on MLOps‐style workflows (experiment tracking, serving, monitoring) and shipping with engineers Able to communicate uncertainty and model limitations clearly ...

shipping models to production and supporting them post-deployment. Strong Python programming skills, including object-oriented design and proficiency with key ML libraries (e.g., PyTorch, TensorFlow, Scikit-Learn). Solid understanding of probability and statistical modeling to support robust model development and interpretation. Experience with cloud platforms (especially Azure ...