1 to 25 of 26 Permanent Amazon SageMaker Jobs in London

Docker, Kubernetes) to operate, support, and secure mission-critical applications Preferred qualifications, capabilities and skills Experience with MLOps tools and platforms such as MLflow, Amazon SageMaker, Google VertexAI, Databricks, BentoML, KServe, and Kubeflow Exposure to cloud-native microservices architecture Familiarity with advanced AI/ML concepts and protocols ...

deploying Machine Learning models using Python Experience with frameworks such as PyTorch, TensorFlow, Scikit-learn or XGBoost Knowledge of AWS cloud services including SageMaker, Lambda and S3 Experience with MLOps tools such as MLflow, Weights & Biases or Data Version Control Experience designing, testing and evaluating machine learning experiments Knowledge ...

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 or GCP; experienced with containerisation, IaC, event ...

serving: NVIDIA Triton, vLLM, TensorRT-LLM, or equivalent high-throughput serving platforms. MLOps/LLMOps: Kubeflow, MLflow, and at least one hyperscaler ML platform (SageMaker, Azure ML, or Vertex AI). Generative AI: LLM fine-tuning (LoRA/QLoRA), RAG architecture design, vector databases (Pinecone, Milvus, Weaviate), and agentic ...

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). Platform & Cloud Engineering: Architecture and delivery of scalable cloud data and AI platforms on AWS, Azure or GCP; experienced with ...

tooling exposure (LangChain, LlamaIndex, vector databases such as Pinecone, Weaviate or pgvector, RAG patterns, fine-tuning workflows) MLOps platforms (MLflow, Kubeflow, Vertex AI, SageMaker, Databricks or equivalent) Cloud experience (AWS, GCP, Azure), containerisation and basic data engineering/SQL Familiarity with experimentation, A/B testing and online evaluation ...

. Hands‐on experience with GCP Vertex AI (model endpoints, pipelines, embeddings, vector search) or equivalent cloud‐native AI/ML platforms (e.g. AWS SageMaker, AzureML) and agent orchestration frameworks (e.g. LangChain, LangGraph, ADK). Solid understanding of MLOps – CI/CD, IaC (Terraform), experiment tracking, model registry ...

using Docker and Kubernetes. Engineering: Strong software engineering fundamentals, including version control, testing, and API/microservices architecture. Experience with MLOps platforms (e.g., MLflow, SageMaker) or agentic AI frameworks. Familiarity with secure development practices or regulated/high-compliance environments. Background in NLP, computer vision, or data engineering platforms. ...

equivalents in Azure or GCP), with hands‐on work across classical ML and modern LLM/RAG systems using services like Amazon SageMaker and Bedrock. What you’ll do Partner with stakeholders across the business to explore high‐impact opportunities. Own the full lifecycle: problem framing, data discovery … building RAG systems. Orchestration: for example LangChain for pipelines/agents. RAG best practices and evaluation workflows (e.g., agentic/RAG patterns on SageMaker). Comfortable choosing the right technique for the job (from baselines to advanced models), with an emphasis on measurable impact and maintainability. Clear communication with ...

optimization frameworks (AutoPrompt, DSPy) and building evaluation suites. Experience with distributed computing, data sharding, and performance optimization. Hands-on with AWS AI deployment services (SageMaker, Bedrock) and workflow orchestration. Demonstrated experience in financial services, particularly investment banking operations. ABOUT US J.P. Morgan is a global leader in financial services ...

documentation and collaborate across engineering teams. Ecosystem Knowledge : Hands‐on experience supporting software delivery and MLOps tooling (e.g., Kubernetes, Kubeflow, MLflow, Triton, Docker, or SageMaker/Azure ML). Equal Opportunity Statement We are committed to fostering and promoting an inclusive professional environment for all of our employees ...

documentation and collaborate across engineering teams. Ecosystem Knowledge : Hands-on experience supporting software delivery and MLOps tooling (e.g., Kubernetes, Kubeflow, MLflow, Triton, Docker, or SageMaker/Azure ML) Equal Opportunity Statement We are committed to fostering and promoting an inclusive professional environment for all of our employees ...

Familiarity with cloud‐based application development (AWS & Azure). Familiarity with one or more ML frameworks and technologies: scikit‐learn, xgboost, TensorFlow, PyTorch, Spark, SageMaker, Vertex AI, Kubeflow, Seldon, Triton. Strong communication skills, able to express ideas clearly and collaborate across teams. #J-18808-Ljbffr ...

frameworks (e.g., Python, .NET, APIs, approved SDLC and web frameworks). Design secure and scalable integrations with AWS services such as S3, Redshift, SageMaker, EC2, IAM, and VPC. Cloud, Security & Governance Ensure applications meet security, risk, and data protection requirements, including SSO/MFA, encryption, segregation of duties ...

expand from a GCP‐first environment to a hybrid AWS and GCP architecture. Define GPU compute strategy across Kubernetes, Vertex AI and SageMaker, balancing performance, scalability and cost efficiency. Drive the production adoption of Generative AI and LLM capabilities, establishing best practices for evaluation, deployment, experimentation and governance. Collaborate ...

models into production, balancing quick wins with robust engineering. Focus areas include AI/OCR workflows, RAG systems, and deploying models on AWS with SageMaker/Bedrock. This hybrid role requires 1–2 days in Central London per week and right to work in the UK. #J-18808-Ljbffr ...

demonstrate excellent technical capabilities, including proficiency in Python, SQL and Git. Practical experience deploying machine learning models within cloud-based environments, particularly using AWS SageMaker, will be highly advantageous. Candidates should possess a solid understanding of statistical modelling techniques and demonstrate a genuine enthusiasm for machine learning, predictive analytics ...

provide technical leadership across the full lifecycle of machine learning systems while architecting production-grade ML solutions. You will work with AWS SageMaker, lead teams on MLOps strategies, and ensure systems adhere to governance standards. This is a hands-on, technical position ideal for those with deep expertise ...

ground up that create lasting leverage across the entire engineering organisation Work at the Frontier: Get hands‐on with the latest AWS capabilities, including SageMaker Unified Studio, Bedrock, and beyond, in a stack that’s modern by design, not by accident Own It End‐to‐End: From … this role has real scope. No tickets, no hand‐offs, just ownership What You Bring AWS Depth: Strong production experience with Lambda, ECS, S3, SageMaker, and Bedrock, with solid knowledge of IAM, cloud networking, and security fundamentals Terraform Expertise: Deep, hands‐on Terraform experience. You write infrastructure‐as‐code ...

model monitoring, content safety, LLMOps, GenAIOps or production support for AI systems Experience with non‐Microsoft AI platforms or services, such as AWS Bedrock, Amazon Q, SageMaker, Google Vertex AI, Anthropic Claude, OpenAI APIs or open‐source model ecosystems Familiarity with ISO 42001, NIST ...

collaborate with enterprise teams to align with standards. The role requires hands-on development in Python and .NET, experience with AWS services (S3, Redshift, SageMaker, EC2, IAM, VPC), and a track #J-18808-Ljbffr ...

Citi's COO Technology organization is building one of the most consequential AI platforms in global financial services — and this is the role that leads it. The Head of AI Solutions is a newly created ...

models and drive business insights.Be a Databricks champion or have some Databricks certificationsAWSWork hands-on with AWS services such as Redshift, Glue, Lake Formation, SageMaker, Athena, and moreStrong hands-on expertise with AWS services (e.g. Redshift, Glue, Lake Formation, SageMaker).AWS Certified ArchitectAdditional InfoSecurity Clearance: To be successfully ...

design authority Comfortable working directly with senior client stakeholders Strong mentoring and coaching capability Experience with some of the following technologies or ecosystems: Amazon Bedrock and SageMaker Claude/Anthropic Azure AI Foundry or Azure OpenAI Databricks Vector databases and RAG architectures Agentic AI orchestration frameworks ...

Role Summary We are seeking a Principal Machine Learning Engineer (SageMaker, MLOps, Model Governance & Explainability) to provide technical leadership across the full lifecycle of machine learning systems powering a new matching platform. This role is accountable for defining ML architecture, establishing engineering standards, driving MLOps maturity, and ensuring that … platform, including data pipelines, model training workflows, inference runtimes, and telemetry ecosystems. Lead adoption of best‐in‐class MLOps patterns, platform tooling, and AWS SageMaker capabilities across training, processing, registry, monitoring, and deployment. Partner with platform, security, and data engineering teams to implement scalable data lakehouse oriented feature architectures ...