1 to 25 of 26 Amazon SageMaker Jobs in the UK excluding London

Milvus) and embedding technologies Expert in building RAG (Retrieval-Augmented Generation) systems at scale Strong experience with MLOps practices and model deployment pipelines Proficient in cloud AI services (AWS SageMaker/Bedrock) Deep understanding of distributed systems and microservices architecture Expert in data pipeline platforms (Apache Kafka, Airflow, Spark) Proficient in both SQL (PostgreSQL, MySQL) and NoSQL (Elasticsearch, MongoDB More ❯

Milvus) and embedding technologies Expert in building RAG (Retrieval-Augmented Generation) systems at scale Strong experience with MLOps practices and model deployment pipelines Proficient in cloud AI services (AWS SageMaker/Bedrock) Deep understanding of distributed systems and microservices architecture Expert in data pipeline platforms (Apache Kafka, Airflow, Spark) Proficient in both SQL (PostgreSQL, MySQL) and NoSQL (Elasticsearch, MongoDB More ❯

top-tier performance. Collaborating with cross-functional teams (data scientists, software engineers, product managers) to turn business needs into technical solutions. Building and maintaining scalable ML pipelines using AWS (SageMaker, EC2, S3, Lambda, Rekognition). Staying up to date with the latest in ML and computer vision research and applying new techniques to real-world challenges. Contributing to the More ❯

SQL, DAX, Python (Pandas, NumPy, Scikit-learn - desirable) CRM Systems : Salesforce, HubSpot, Dynamics 365, Zoho ETL Tools : dbt, Fivetran, Talend, Alteryx AI/ML Frameworks (Desirable): Azure ML, AWS Sagemaker, HuggingFace, OpenAI APIs Version Control & DevOps : Git, Azure DevOps, GitHub Actions What We're Looking For Essential 2+ years' experience in a BI, data analyst, or similar analytics role More ❯

SQL, DAX, Python (Pandas, NumPy, Scikit-learn - desirable) CRM Systems : Salesforce, HubSpot, Dynamics 365, Zoho ETL Tools : dbt, Fivetran, Talend, Alteryx AI/ML Frameworks (Desirable): Azure ML, AWS Sagemaker, HuggingFace, OpenAI APIs Version Control & DevOps : Git, Azure DevOps, GitHub Actions What We're Looking For Essential 2+ years' experience in a BI, data analyst, or similar analytics role More ❯

SQL, DAX, Python (Pandas, NumPy, Scikit-learn - desirable) CRM Systems : Salesforce, HubSpot, Dynamics 365, Zoho ETL Tools : dbt, Fivetran, Talend, Alteryx AI/ML Frameworks (Desirable): Azure ML, AWS Sagemaker, HuggingFace, OpenAI APIs Version Control & DevOps : Git, Azure DevOps, GitHub Actions What We're Looking For Essential 2+ years' experience in a BI, data analyst, or similar analytics role More ❯

SQL, DAX, Python (Pandas, NumPy, Scikit-learn - desirable) CRM Systems : Salesforce, HubSpot, Dynamics 365, Zoho ETL Tools : dbt, Fivetran, Talend, Alteryx AI/ML Frameworks (Desirable): Azure ML, AWS Sagemaker, HuggingFace, OpenAI APIs Version Control & DevOps : Git, Azure DevOps, GitHub Actions What We're Looking For Essential 2+ years' experience in a BI, data analyst, or similar analytics role More ❯

SQL, DAX, Python (Pandas, NumPy, Scikit-learn - desirable) CRM Systems : Salesforce, HubSpot, Dynamics 365, Zoho ETL Tools : dbt, Fivetran, Talend, Alteryx AI/ML Frameworks (Desirable): Azure ML, AWS Sagemaker, HuggingFace, OpenAI APIs Version Control & DevOps : Git, Azure DevOps, GitHub Actions What We're Looking For Essential 2+ years' experience in a BI, data analyst, or similar analytics role More ❯

data science roles, preferably in fast-moving or early-stage environments Languages & Tools: Strong Python (Pandas, NumPy, Scikit-learn, TensorFlow or PyTorch) Advanced SQL AWS MLOps tooling (e.g., MLflow, SageMaker, or similar) Bonus Points For: Knowledge of LLMs, RAG pipelines, prompt engineering, or agentic interfaces Experience with data warehouse tools (Snowflake, Redshift, BigQuery) Familiarity with search, matching, or recommendation More ❯

data science roles, preferably in fast-moving or early-stage environments Languages & Tools: Strong Python (Pandas, NumPy, Scikit-learn, TensorFlow or PyTorch) Advanced SQL AWS MLOps tooling (e.g., MLflow, SageMaker, or similar) Bonus Points For: Knowledge of LLMs, RAG pipelines, prompt engineering, or agentic interfaces Experience with data warehouse tools (Snowflake, Redshift, BigQuery) Familiarity with search, matching, or recommendation More ❯

into DV and undertake occasional overseas assignments • Strong team player with a proactive mindset, eager to shape new delivery teams Desirable Skills • Exposure to cloud ML platforms (e.g., AWS Sagemaker, Azure ML) • Experience deploying data/API services and microservice architectures • Previous consulting or defence/national security sector experience • Familiarity with Ansible or similar configuration management tooling Package More ❯

image processing workflows, deep learning pipelines, and model evaluation. Familiarity with MLflow for tracking experiments, managing model lifecycle, or deploying models. Experience with AWS services such as S3, EC2, SageMaker, Lambda, or similar tools for model deployment and data pipelines. What you'll be doing: Research and develop solutions to complex business problems, working with large, unstructured datasets. Apply More ❯

modern frameworks. Build and optimize RAG pipelines using models like GPT, Claude, or other LLMs integrated with document retrieval systems. Develop production-ready ML applications in cloud environments (AWS, SageMaker, Databricks, etc.). Leverage GPU-based computing resources and CUDA/Nvidia for performance optimization in training and inference. Collaborate with data engineers, software developers, and product teams to … experience with PyTorch, TensorFlow, Scikit-learn, and transformer-based models. Practical knowledge of LLM integration (e.g., GPT, Claude) and RAG architecture. Experience with ML lifecycle management tools like AWS SageMaker, MLflow, or Databricks. Working knowledge of CUDA, Nvidia GPUs, and distributed training. Experience with AWS services (S3, Lambda, EC2, SageMaker, Bedrock, etc.). Desired: Experience deploying models as More ❯

and development to succeed. A progressive organisation where you can really make a difference. We a great opportunity for a Data Scientist. You will have solid experience of Bedrock, Sagemaker, Python and Pandas. Key Responsibilities: * Working experience LLMs under Bedrock and Sagemaker both Amazon * Python with APIs to ChatGPT * Strong coding skills using libraries like pandas, NumPy … Experience: AWS Data Science Environment: Hands-on experience with Sage Maker, Lambda, Step Functions, S3, Athena. Model deployment and pipeline orchestration in AWS. OCR Use-Case Development: Proficiency with Amazon Tex-tract, Tesseract, and LLM-based OCR. Building document parsing pipelines, validations, and rule Python Proficiency: Strong coding skills using libraries like pandas, NumPy, scikit-learn, PyTorch, and Hugging … actionable insights. Stakeholder Collaboration: Effective communication with technical and non-technical stakeholders. Experience in cross-functional team. Data Engineering Basics: Familiarity with SQL and big data processing tools (e.g., Amazon Athena). Model Evaluation & Experimentation: A/B testing, statistical analysis, and performance metrics. Security & Compliance Awareness: Understanding of data privacy, PII handling, and compliance standards (e.g., GDPR). More ❯

value: • Cloud platform deployment on AWS or Azure • Containerisation using Docker or Kubernetes • Experience with Ansible or other configuration management tools • Exposure to machine learning platforms (Azure ML, TensorFlow, Amazon SageMaker) • Working with relational or NoSQL databases (document, graph, or RDBMS) Platform Engineer - Key Benefits: • Clear career progression within the National Security & Gov space • Flexible hybrid working & generous More ❯

TensorFlow, PyTorch, or Hugging Face Solid understanding of machine learning fundamentals and performance evaluation techniques Experience working in cloud platforms (AWS, GCP, or Azure) with MLOps tools (e.g. MLflow, SageMaker, Vertex AI) Comfortable working independently and delivering high-quality work to tight timelines Experience working in fast-paced environments or scale-up settings Company Market leading financial services (fintech More ❯

solutions in complex enterprise environments Experience in all architecture domains:- application, data, cloud ( AWS) and technology with expertise with AI, Gen Ai and ML frameworks (e.g., TensorFlow, PyTorch, AWS Sagemaker, AWS Bedrock, OpenAI). Strong experience of AI services and AI lifecycle and model training Proficiency in backend and frontend technologies such as .NET Core, Node.js, and React; familiarity More ❯

Have technical expertise in one or more of the following technology areas: NoSQL, such as DocumentDB/MongoDB RDF Graph database such as GraphDB ML/AI such as Sagemaker/Bedrock Search technologies such as SOLR or Opensearch/ElasticSearch Data pipeline engineering utilising cloud-based technologies (AWS) Write high quality clean, testable code, with a focus on More ❯

for data science and model development Excellent attention to detail and data quality Clear communication skills and ability to explain complex concepts Familiarity with cloud technologies like AWS and Sagemaker is advantageous Ability to work independently and collaboratively within a team TO BE CONSIDERED. Please either apply by clicking online or emailing me directly to . For further information More ❯

using emerging technologies on client deliveries and through research. We are looking for experience in the following skills and experience: AI/ML platform technologies and services such as Sagemaker/Vertex/Azure ML, OpenAI, Langchain, AutoML, OCR, STT, feature stores, vector DB, ... Implementation of AI/ML architectural patterns and best practices e.g. data drift detection More ❯

collaborate across disciplines. Experience and skills we'd love: Familiarity with MLflow for tracking experiments, managing model lifecycle, or deploying models. Experience with AWS services such as S3, EC2, SageMaker, Lambda, or similar tools for model deployment and data pipelines. Computer Vision Expertise: Practical experience or exposure to modern computer vision models and techniques such as ResNet, YOLO, Vision More ❯

technologies based on client delivery experience and research Qualification We are looking for experience in the following skills and experience: AI/ML platform technologies and services such as Sagemaker/Vertex/Azure ML, OpenAI, Langchain, AutoML, OCR, STT, feature stores, vector DB, AI/ML architectural patterns and best practices e.g. data drift detection, experimentation tracking, RAG More ❯

mentored by a friendly development team, and the BBC will provide many opportunities for learning as you progress. We create and support reliable and scalable cloud-based services on Amazon Web Services, use GitHub for version control and practice pair programming and Test-Driven Development where possible. Hands-on experience with Python development and an understanding of software engineering … best practices (e.g., TDD, clean code principles). Experience of AWS services such as SageMaker, S3, EC2, VPC, Lambda, Redshift Experience of DevOps practices, including containerisation with Docker and CI/CD pipelines. Exposure to MLOps tools (e.g., MLFlow) and practices, with a willingness to learn more. Exposure to infrastructure-as-code tools (CDK, CloudFormation) Knowledge of feature engineering More ❯

multi-modal models that combine vision and language Strong grasp of data-centric AI practices - annotation tooling, prompt evaluation, and dataset curation Familiarity with MLOps tools (e.g. Weights & Biases, SageMaker, MLflow) Experience working in regulated sectors like insurance, banking, or property What You'll Be Doing This is a hands-on, high-impact role - you'll be building production … image segmentation Apply NLP to real-world business problems - summarisation, entity recognition, information extraction, and more Train and deploy models at scale using AWS - including Lambda, EC2, S3, and SageMaker Meet with enterprise clients to explore problems, present ideas, and share results Prototype fast, test often, and get working solutions into the hands of users Work cross-functionally with More ❯

Description 9 Months Fixed Term Contract The Data Science role is responsible for using Data Science and modelling techniques to address critical questions for both the business and our customers. This includes understanding the challenges our customers face with regards More ❯