1 to 25 of 122 Permanent PyTorch Jobs in London

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 ...

with frameworks such as NumPy, Pandas, Scikit-learn, and modern Generative AI libraries (e.g., LangChain, LlamaIndex, Azure AI Foundry). Hands‐on experience with PyTorch, leading LLM libraries such as Hugging Face, LangChain, LangGraph, and LlamaIndex. Skilled in hypothesis formulation, defining evaluation metrics, conducting literature reviews and building reproducible prototypes ...

several of the following: Commercial experience developing AI or Machine Learning solutions Strong Python development skills Experience with Machine Learning frameworks such as TensorFlow, PyTorch or Scikit-learn Experience with Generative AI technologies including LLMs, LangChain or LlamaIndex Hands-on experience building RAG solutions and working with vector databases Experience ...

/CD, containerisation, monitoring, and deployment automation. Proficiency in Python and/or R, with experience using machine learning frameworks such as TensorFlow, PyTorch, and scikit-learn. Experience with modern AI frameworks such as FastAPI, LangChain, LlamaIndex, or similar technologies. Hands-on experience with LLM APIs, foundation models, embeddings, vector ...

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 ...

/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 ...

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 ...

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 ...

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 ...

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. ...

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 ...

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 ...

modern software development practices. Hands‐on experience with Distributed Training infrastructure (Multi‐node GPU training, Kubernetes, vLLM). Familiarity with Deep Learning frameworks (PyTorch). Experience with MLOps tools and experiment tracking (e.g., ClearML, MLFlow, Weights & Biases). Research Fluency: Ability to read technical research papers and translate them into ...

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 ...

methods. Familiarity with rigorous experimentation: online/offline evaluation, data leakage prevention, and model governance. Tech Stack Python, SQL, pandas/numpy/scipy, PyTorch/sklearn Airflow/dbt, Kafka (or equivalents), Postgres/BigQuery Docker, Kubernetes (optional), CI/CD (GitHub Actions) Observability: Prometheus/Grafana, OpenTelemetry ...

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 ...

Language Model (LLM) deployment and hosting Retrieval Augmented Generation (RAG), vector databases, semantic search and embedding techniques Python development and AI frameworks such as PyTorch, TensorFlow and LangChain MLOps frameworks and AI model lifecycle management API integration and enterprise-wide AI solution delivery Presenting architecture solutions to senior stakeholders, governance ...

containerised application experience Infrastructure as code experience, ideally Terraform or CloudFormation Experience with SQL, PySpark, Databricks or AWS Glue Exposure to Scikit‐learn, PyTorch, LightGBM or similar libraries An understanding of LLMs, multimodal models or generative AI applications Deep commercial LLM experience is not essential. The hiring manager is more ...

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 ...

system integrations — with a strong focus on GenAI, NLP, computer vision, and multimodal AI applications. Leverage deep knowledge of AI/ML frameworks (e.g., PyTorch, TensorFlow, Hugging Face) and enterprise architecture best practices (e.g., microservices, APIs, cloud-native design). AI & Data Platform Architecture/Deployment: Architect robust, secure ...

technologies including Generative AI and Large Language Models. Required Experience: Commercial AI or Machine Learning experience. Strong Python and SQL skills. Experience with TensorFlow, PyTorch or similar frameworks. Understanding of machine learning and model deployment. Experience with Azure, AWS or GCP. Knowledge of data pipelines, ETL and MLOps. Strong analytical ...

data, especially large-scale text or content datasets. Familiarity with common data science and machine learning tools such as Pandas, NumPy, SciPy, Scikit-learn, PyTorch, TensorFlow, or Matplotlib. The ability to translate complex and ambiguous requirements into practical, measurable, data-driven solutions, with strong analytical thinking, problem-solving skills ...

retrieval orchestration Evaluation datasets, benchmarking, and annotation workflows Advanced programming skills in Python. Experience with modern AI/ML frameworks and tooling (e.g., PyTorch, Hugging Face, LangChain, LangGraph, Haystack). Experience working with large-scale datasets, distributed data/ML platforms, and production AI systems. Strong understanding of statistical analysis ...

EMNLP, NAACL, ICLR) with specific focus on agent systems, tool use, or multi‐agent coordination. Familiarity with one or more deep learning frameworks (e.g. pytorch, jax, tensorflow, ...) Experience in ML Research beyond completing a PhD (e.g. supervision, industry experience, leading academic initiatives, ...). Excellent communication skills to report ...