1 to 25 of 114 PyTorch Jobs in London

implementation experience NLP and Conversational AI development Model training, testing and evaluation Prompt Engineering and AI workflow optimisation Programming & Frameworks Strong Python development skills PyTorch TensorFlow Scikit-Learn LangChain LangGraph Hugging Face FastAPI REST APIs Data Technologies SQL NoSQL Databases Data Modelling ETL Development Data Pipeline Engineering Vector Databases such ...

Bring Technical Expertise: Strong Python skills with the ML stack: NumPy, pandas, scikit-learn Hands-on experience with at least one deep learning framework (PyTorch, TensorFlow, JAX) Solid grounding in core ML—supervised, unsupervised, evaluation, regularisation, statistics Production ML experience—deploying, serving and monitoring models at scale LLM and generative ...

bring experience in managing, coaching, and developing junior members of a team and wider community. Desirable Demonstrable experience with modern deep learning frameworks (e.g. PyTorch, TensorFlow), fine‐tuning or distillation of LLMs (e.g, GPT, Llama, Claude, Gemini), machine learning libraries (e.g. scikit‐learn, XGBoost). Experience with data storage ...

coaching, and developing junior members of a team and wider community. \n\n DESIRABLE: \n \n Demonstrable experience with modern deep learning frameworks (e.g. PyTorch, TensorFlow), fine-tuning or distillation of LLMs (e.g, GPT, Llama, Claude, Gemini), machine learning libraries (e.g. scikit-learn, XGBoost). \n\n \n Experience with ...

/fairness and emerging regulations. Machine Learning Mastery – profound understanding of ML principles, algorithms, frameworks, and training pipelines. Technical Proficiency – programming in Python, TensorFlow, PyTorch or similar; modern LLM/agent frameworks; cloud AI platforms (Amazon Bedrock, Azure OpenAI/AI Foundry, Google Vertex AI); vector databases; containerization and orchestration ...

Oversee the design and deployment of enterprise-grade AI solutions using Python , .NET , and cloud-based MLOps pipelines. Direct teams leveraging advanced frameworks including PyTorch , TensforFlow , Hugging Face , ONNX Runtime , and LangChain , integrating orchestration tools like Semantic Kernel , LangGraph , and CrewAI Drive responsible integration of Large Language Models (LLMs) from ...

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 ...

Requirements Vetting: Active SC Clearance and British Citizenship are mandatory for this consultancy role. Core Tech: Solid professional experience with Python and frameworks like PyTorch, TensorFlow, or Scikit-Learn. GenAI: Hands-on experience developing LLM-based applications, RAG pipelines, and prompt engineering. Infrastructure: Experience deploying applications in cloud environments ...

large-scale production environments.Experience with MLOps practices and tools for managing the machine learning lifecycle.Proficiency in Python and machine learning frameworks such as PyTorch, TensorFlow, and scikit-learn.Strong understanding of data preprocessing, feature engineering, and evaluation techniques.Experience working with large, complex datasets and applying statistical analysis.Familiarity with cloud platforms ...

deploying AI applications in large scale production environments. Experience managing data science teams and couching team members Proficiency in Python and ML frameworks (PyTorch, TensorFlow, scikit-learn). Hands-on experience with agentic frameworks (LangChain, CrewAI, AutoGen, LangGraph, ADK). Experience with generative models (transformers, GANs/VAEs; diffusion models ...

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 ...

adoption and ensure clients receive the most relevant, timely, and actionable content. You will utilize technologies including Python (Pandas, Polars, Scikit‐learn, TensorFlow/PyTorch), Jupyter, Trino, SQL, and gain exposure to graph database technologies. RESPONSIBILITIES AND QUALIFICATIONS Responsibilities: Design, build, and maintain robust data pipelines for feature engineering ...

engineering, model training, evaluation and production deployment, including MLOps, monitoring and drift detection. \n\n \n Practical knowledge of ML frameworks (e.g. scikit-learn, PyTorch, XGBoost) and cloud-native ML services (SageMaker, Azure ML, Vertex AI). \n\n Platform & Cloud Engineering: \n \n Architecture and delivery of scalable cloud ...

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 ...

adoption and ensure clients receive the most relevant, timely, and actionable content. You will utilize technologies including Python (Pandas, Polars, Scikit‐learn, TensorFlow/PyTorch), Jupyter, Trino, SQL, and gain exposure to graph database technologies. RESPONSIBILITIES Design, build, and maintain robust data pipelines for feature engineering and model training, ensuring ...

retrieval‐augmented generation, tool/function calling, agentic workflows), including evaluation and safety patterns. Expertise with machine learning frameworks and data science packages (e.g., PyTorch, TensorFlow, Scikit‐Learn, NumPy, Pandas, SciPy, statsmodels). Experience deploying to AWS (e.g., SageMaker, Bedrock) and operating production workloads with attention to cost, performance, security ...

with experience in data manipulation, model development, and analytical workflows. Hands‐on experience with machine learning frameworks such as scikit‐learn, TensorFlow, PyTorch, or similar. Strong experience with cloud platforms (AWS, Azure, or GCP) and building cloud‐native systems. Experience with modern data platforms such as Snowflake, BigQuery, or Databricks. ...

interest in NLPBroad knowledge of MLOps tooling - for versioning, reproducibility, observability etc.Experience monitoring, maintaining, enhancing existing models over an extended time periodExtensive 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 ...

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

frameworks. Strong proficiency in programming languages such as Python, Java, or Go, along with experience integrating with relevant AI/ML frameworks (e.g., TensorFlow, PyTorch). Proven ability to translate complex business requirements into well‐defined, cloud‐optimized application architectures, scalable data models (e.g., relational, NoSQL, graph), and technical specifications ...

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 ...

Computer Science, Data Science, Machine Learning, or related field. \nExperience 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 such ...

practices, covering the full cycle from design, experimentation, deployment, to monitoring and maintenance of machine learning models.Expertise in machine learning frameworks such as TensorFlow, PyTorch, PyTorch Lightning, or Scikit-learn.Proficiency in Python with a strong emphasis on code quality and reliability through comprehensive testing.Extensive experience with generative AI models, mainly ...

Learning and ideally Azure AI Foundry Good understanding of MLOps and LLMOps Excellent Python engineering skills with experience using frameworks such as LangChain, LangGraph, PyTorch and Pydantic Experience with RAG, vector search, embeddings, prompt engineering and enterprise retrieval architectures Experience building AI solutions within document-heavy environments such as legal ...

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 ...