1 to 25 of 39 Amazon SageMaker Jobs in the UK

/ML engineering, shipping models in production • 3+ years in a Staff-level or senior technical leadership role • Hands-on AWS (Bedrock, SageMaker) and/or GCP Vertex AI • Strong Python; Java or Rust a bonus • Experience with LLMs, evaluation frameworks, and agentic AI patterns • Docker, K8s, Terraform …/CD • A collaborative leadership style — mentoring engineers, shaping best practices ────────────────────────── Core stack: Python · Rust · Java · Amazon Bedrock · SageMaker · Vertex AI · LangGraph · Pydantic AI · LangFuse · MLFlow · Databricks · Datadog · Claude Code · Docker · K8s · Terraform · Vector DBs · Graph DBs ────────────────────────── UK Remote Competitive Salary and benefits Not eligible for visa sponsorship ...

pipelines, and custom model fine-tuning. Working closely with architects and data teams, you will turn conceptual designs into robust, production-grade software using Amazon Bedrock and modern Python frameworks. Key Responsibilities · Agent Development: Build and deploy sophisticated AI agents using Python, LangChain, and LangGraph. Implement tool calling (function … calling), memory persistence, and error-handling logic for robust autonomous execution. · RAG Implementation: Develop high-performance retrieval pipelines. Optimise chunking strategies, embedding generation (using Amazon Titan or similar), and vector search retrieval in Amazon OpenSearch. · Model Fine-Tuning: Execute fine-tuning jobs on Amazon SageMaker, preparing ...

language models. Strong grounding in ML concepts — supervised, unsupervised, and reinforcement learning. Familiarity with cloud AI/ML services (e.g. Azure Cognitive Services, AWS SageMaker, and/or GCP Vertex AI). Experience deploying and monitoring AI workloads in CI/CD environments (e.g. Jenkins, Docker, Kubernetes, and/ ...

Docker, Kubernetes desirable) Model packaging and REST APIs Cloud & Tools (Any combination) AWS/Azure/GCP analytics and ML services MLflow, Azure ML, SageMaker, Vertex AI Version control (Git) Domain & Soft Skills Strong analytical and problem solving skills Ability to explain complex data science concepts in simple business ...

science Strong Python skills with experience in ML frameworks such as scikit-learn, PyTorch, TensorFlow, or XGBoost Exposure to AWS services (e.g. S3, Lambda, SageMaker) Understanding of core ML concepts: model evaluation, validation, and experimentation Familiarity with MLOps or experiment tracking tools (e.g. MLflow, Weights & Biases) Awareness of LLMs ...

/CD pipelines. You can set up APIs, write robust code, and debug pipelines. ● Experience with cloud-native ML workflows, including AWS Sagemaker, Lambda, ECS, and containerisation with Docker. ● Familiarity with frontend collaboration—how your model outputs can drive dynamic UIs, content personalization, or editor tools. ● Comfort in “hacking ...

across one or more CSPs or third-party vendor technologies, including Google PaLM and Vertex AI, Azure OpenAI Services and AzureML, AWS Bedrock and Sagemaker, Dataiku, Databricks, Snowflake SnowPark and Snowflake Cortex, Data Robot. Experience in architecting scalable, performant & cost optimized AI/ML solutions leveraging; serverless technologies, container ...

across one or more CSPs or third-party vendor technologies, including Google PaLM and Vertex AI, Azure OpenAI Services and AzureML, AWS Bedrock and Sagemaker, Dataiku, Databricks, Snowflake SnowPark and Snowflake Cortex, Data Robot. Experience in architecting scalable, performant & cost optimized AI/ML solutions leveraging; serverless technologies, container ...

Agile or Scrum methodologies is beneficial. The role will principally centre on MLFlow as an MLOps platform, but similar experience in platforms such as SageMaker or VertexAI is a definite benefit. The Company Optima Partners is an advanced data and business consultancy headquartered in Edinburgh, UK. ...

Weaviate, FAISS , Qudrant) Agentic AI frameworks (exposure to LangGraph, AutoGen, CrewAI or others) Exposure to cloud AI platforms (Azure AI Foundry, AWS Bedrock/SageMaker, GCP Vertex AI). Understanding of basic Responsible AI principles and safe deployment patterns. Ability to collaborate with cross-functional teams and contribute ...

NumPy, Pandas, SciPy, Scikit‐learn, TensorFlow, PyTorch, Transformers, Langchain, Streamlit, or Gradio, among others. Experience with cloud‐based tools for production use (e.g., AWS SageMaker, AWS Bedrock, Vertex AI, Azure Machine Learning, Azure OpenAI). Knowledge of databases and data technologies, such as Snowflake, BigQuery, and relational databases like ...

some of the following tools; Apache Spark, Databricks, Pandas for data processing and feature engineering SQL, MongoDB for structured and unstructured data management SageMaker, Azure ML for model deployment, tracking, and monitoring. Terraform, Ansible, GitLab CI/CD, Jenkins for infrastructure automation and DevSecOps ...

deploying ML models in Python using frameworks such as scikit-learn, XGBoost, PyTorch, or TensorFlow Strong experience with cloud-based ML deployment (e.g., AWS SageMaker, Lambda, S3) Knowledge of MLOps/LLMOps tooling (e.g., MLflow, Weights & Biases, Data Version Control) Experience developing LLM/GenAI applications, including prompt engineering ...

Generative AI models, LLMs, and agentic frameworks. •Collaborate with stakeholders to define problem statements and solution approaches. •Deploy models using MLOps tools such as SageMaker, Snowflake, and CI/CD pipelines. •Integrate vector databases and Retrieval-Augmented Generation (RAG) pipelines. •Ensure high-quality delivery and adherence to best practices ...

/ML engineering, with hands-on experience in LLMs Strong programming skills in Python Proven experience working with AWS (e.g. S3, Lambda, SageMaker, ECS) Experience delivering solutions for UK Central Government projects Active SC (Security Check) Clearance (must be current and transferable) Solid understanding of machine learning lifecycle, model ...

Degree in a relevant technical field Tech Environment Python, Java Cloud platforms AWS Containerisation and infrastructure-as-code tools Relational and non-relational databases Amazon Bedrock, Sagemaker, Vertex AI Datadog, Databricks, MLFlow, Grafana, OTel Claude, Gemini, ChatGPT, open-weight LLM models Terraform, Docker, K8s RMDBs, Graph DBs, Vector ...

Python and SQL skills Understanding of data platforms (eg Snowflake/CDP) and ingestion pipelines Exposure to AI/ML enablement frameworks (.eg AWS SageMaker) and supporting infrastructure for model training, deployment Experience with dbt/ELT patterns (beneficial, not core focus) Strong stakeholder communication and technical leadership skills ...

facing or product-centric ML systems. A product-focused mindset, balancing experimentation with real-world value. Useful additional experience includes: AWS or GCP environments (SageMaker, Bedrock, Lambda, S3, Redshift). MLOps practices (monitoring, deployment, optimisation). Working with streaming data, transformer models or recommendation systems. What They Offer ...

technical audiences. Understanding of Information Governance, ethics, and AI explainability. Excellent problem-solving, organisational, and communication skills. Desirable Cloud computing (Azure ML, AWS SageMaker), APIs, Git Data engineering or DevOps awareness Familiarity with interoperability standards (FHIR, HL7, OpenEHR). Awareness of national data strategies (Data Saves Lives, PHM Framework ...

systems (e.g. RAG, agentic workflows, NLP). Strong product and systems thinking with a practical, impact-led mindset. Nice to Have AWS experience (e.g. SageMaker, Bedrock, Lambda, S3, Redshift). Familiarity with MLOps practices. Background in adtech, media, fraud, or adversarial systems. Why Join Work on technically challenging, high ...

hands-on or architectural experience with modern data platform tooling, including but not limited to Apache Airflow, dbt, Kafka, AWS Glue, AWS Redshift, AWS Sagemaker, AWS Dynamo, AWS Quick Sight. Success leading a data engineering team through complex challenges that are large in scope. Strong knowledge of modern data ...

reliability of ML systems What We're Looking For Proven experience with ML in production environments Strong skills in Python, SQL, and AWS (SageMaker, Lambda, etc.) Experience with NLPs or LLMs Familiarity with MLOps and real-time data applications A pragmatic mindset and strong problem-solving ability Background ...

concepts clearly and effectively to a range of audiences. Experience with model governance, documentation, and deployment best practices. Experience with cloud environments (e.g., AWS Sagemaker). Experience with collaborative development tools (e.g., Git, JIRA) is a plus. Prior experience in financial services, banking, or credit risk modelling is beneficial. ...

Machine learning (supervised & unsupervised) Generative AI & LLMs Embeddings, vector databases, RAG MLOps and model lifecycle management Experience with platforms such as: Azure ML, AWS SageMaker, Google Vertex AI Databricks, LangChain, Hugging Face Ability to develop architecture artefacts (HLDs, solution diagrams, delivery models) Exceptional writing, storytelling, and stakeholder engagement skills ...

ability to design scalable, cloud-native machine learning operations across traditional ML and modern LLM workflows. The ideal candidate will bring experience with SageMaker-based MLOps pipelines, evaluation of equivalent tooling stacks, hybrid MLOps/LLMOps automation, CI/CD orchestration, governance, monitoring, automation and production-grade scalability patterns. … deployment, versioning, monitoring, and CI/CD automation. Build container-oriented ML platforms (EKS-first) while evaluating alternative orchestration tools with similar capabilities (Kubeflow, SageMaker, MLflow, Airflow, etc.). Implement hybrid MLOps + LLMOps workflows, including prompt/version governance, evaluation frameworks, and monitoring for LLM-based systems. Serve ...