10 of 10 Permanent Amazon SageMaker Jobs in London

ML algorithms , NLP , deep learning , and statistical methods. Experience with Docker, Kubernetes , and cloud platforms like AWS/Azure/GCP . Hands-on experience with MLOps tools (MLflow, SageMaker, Kubeflow, etc.) and version control systems. Strong knowledge of APIs, microservices architecture, and CI/CD pipelines. Proven experience in leading teams, managing stakeholders, and delivering end-to-end More ❯

to support decisions across multiple business areas, including marketing, sales, claims, retention, customer behavior, fraud detection, and customer servicing. Deploy machine learning models into production using AWS services, including SageMaker, S3, Feature Store, ensuring scalable, reliable, and monitored solutions that directly support key business processes. Collaborate with product management and engineering teams to integrate data-driven insights and deploy More ❯

HIPAA) Excellent communication, client engagement, and workshop facilitation skills Proven ability to work in matrix environments across global teams Desired skills Exposure to AI platforms like Azure AI, AWS SageMaker, Google Vertex AI Knowledge of PoC packaging and offer development for enterprise clients Experience Experience working with AI CoEs or global delivery teams Benefits Collaborative working environment - we stand More ❯

integration. Familiarity with CI/CD pipelines and modern DevOps workflows. Understanding of authentication, authorization, and web security best practices. Nice-to-haves: Experience deploying ML models using AWS Sagemaker, Hugging Face, or Replicate . Familiarity with WebGL, THREE.js , or other 3D graphics frameworks. Interest in AI, generative models, and spatial computing . More ❯

challenging. You have a voice here and are encouraged to use it. Your experience and career development is in your hands. We live our leadership principles every day. At Amazon, it's always "Day 1". Diverse Experiences Amazon values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the … candidates to apply. If your career is just starting, hasn't followed a traditional path, or includes alternative experiences, don't let it stop you from applying. Why AWS Amazon Web Services (AWS) is the world's most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating - that's why customers from the most … learning or deep learning models and/or systems into production, including batch and real-time data processing - Experience scaling model training and inference using technologies like Slurm, ParallelCluster, Amazon SageMaker - Hands-on experience benchmarking and optimizing performance of models on accelerated computing (GPU, TPU, AI ASICs) clusters with high-speed networking. Our inclusive culture empowers Amazonians to More ❯

LangGraph, LlamaIndex Experience with Hugging Face and LoRA/QLoRA for fine-tuning Experience with RAG & Vector DBs eg. FAISS, Weaviate, Pinecone Any experience of MLOps with MLFlow, AWS (SageMaker), CI/CD (GitHub Actions) or similar would be a benefit to an application The employer is well known not only for the forward-thinking approach they have to More ❯

years experience AWS cloud and AWS services such as Redshift, DMS, RDS, Glue, S3, Athena, Lambda Experience in designing and managing a data warehouse Experience with AWS Bedrock, Sagemaker and PowerBI desirable Strong capability with SQL in both MySQL and Postgresql flavours About You A self-starter looking to make a positive impact in a rapidly evolving environment Ability More ❯

Senior Machine Learning Engineer page is loaded Senior Machine Learning Engineer Apply locations London, UK time type Full time posted on Posted 5 Days Ago job requisition id R15074 Job Title Senior Machine Learning Engineer Job Description Here at UnderwriteMe More ❯

Senior Data Engineer MUST HAVE SNOWFLAKE Salary - £90-100k with 15% bonus Hybrid working - couple of days in the office City of London We are looking for: Good understanding of data engineering principles A good technical grasp of Snowflake More ❯

candidates to apply. If your career is just starting, hasn't followed a traditional path, or includes alternative experiences, don't let it stop you from applying. Why AWS? Amazon Web Services (AWS) is the world's most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that's why customers from the most … Qualifications -Masters or PhD degree in computer science, engineering, mathematics, operations research, or in a highly quantitative field. -Experience building generative AI applications on AWS using services such as Amazon Bedrock and Amazon SageMaker. -Experience with design, deployment, and evaluation of Large Language Model (LLM)-powered agents and tools and orchestration approaches. -Experience with design, development, and optimization … and templates that guide the behavior and responses of LLMs. -Experience with open source frameworks for building applications powered by LLMs like LangChain, LlamaIndex, and/or similar tools. Amazon is an equal opportunities employer. We believe passionately that employing a diverse workforce is central to our success. We make recruiting decisions based on your experience and skills. We More ❯