1 to 25 of 41 Permanent Amazon SageMaker Jobs in London

containerization technologies like docker, Kubernetes, AWS EKS etc.Knowledge of popular Cloud computing vendor (AWS and Azure) infrastructure & services e.g. AWS Bedrock,AWS S3, AWS Sagemaker, Azure AI search, Azure OpenAI, Azure blob storage etc.Master's degree or above in Machine learning/data science, computer science, applied mathematics ...

frameworks.Inference & 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 frameworks ...

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

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). Software Engineering: Production-grade Python services (FastAPI, AWS Lambda, event-driven patterns) and front-end development with React/Next.js ...

good grasp of data engineering lifecycles, ML Ops and LLM Ops.Desirable:Experience with/in: Experience with other cloud provider ML and LLM services (sagemaker, bedrock, langchain, llamaindex, boto3 etc.)Experience with image analysis and extraction tools (Google Cloud Vision, Document Intelligence, MarkItDown)Knowledge of Agentic protocols and their ...

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). Software Engineering: Production-grade Python services (FastAPI, AWS Lambda, event-driven patterns) and front-end development with React/Next.js ...

Proficiency in programming languages such as Python, experience with AI/ML frameworks (e.g., TensorFlow, PyTorch), and experience with MLOps frameworks/tools (e.g. Sagemaker pipelines, Azure ML Studio, VertexAI, Kubeflow, MLFlow, Seldon, EvidentlyAI)What we offerCulture of caring. At GlobalLogic, we prioritize a culture of caring. Across every ...

Kubernetes).Expertise with modern data platforms (e.g., BigQuery/Databricks) and data processing workflows (ETL, pipelines).Excellent experience with cloud hosted AI platforms (Bedrock, Sagemaker, VertexAI)Strong problem-solving abilities, with the capacity to learn quickly and adapt in a fast-paced environment.Excellent communication and a drive to work ...

scikit, pytorch, tidyverse, caret, ggplot, etc.).Proven experience developing, refining, and monitoring NLP models.Familiarity with database management tools and techniques (e.g., SQL, Selenium, S3, Sagemaker, API protocols) is preferred but not required.Understanding model evaluation methods and metrics.Ability to operationalize non-technical ideas into relevant research designs, features, and model ...

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 doPartner with stakeholders across the business to explore high‐impact opportunities.Own the full lifecycle: problem framing, data discovery, feature engineering … methods, and 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 ...

NeedMLOps experience: You’ve operationalised ML models in production, owning deployment, monitoring and lifecycle management.Strong programming: Production-quality, testable Python.Cloud expertise: Deep AWS knowledge (SageMaker, Lambda, ECS/EKS, Step Functions); Snowflake a plus.MLOps tooling: Experiment tracking and registries, workflow orchestration, model serving and feature stores.CI/ ...

strong positive signal. Hands-on production experience with graph neural networks, anomaly detection, or behavioural biometrics, beyond prototyping or fine-tuning. Familiarity with AWS (SageMaker, Lambda, S3, Athena) and CI/CD practices. Experience mentoring or technically guiding other data scientists. Please include a CV in English. Curious ...

Familiarity with prompt optimization frameworks (AutoPrompt, DSPy) and building evaluation suites.Hands-on experience with agentic frameworks (LangChain, LangGraph).Experience with AWS AI deployment services (SageMaker, Bedrock) and workflow orchestration.Demonstrated experience in financial services, particularly investment banking operations.Join us to help shape the future of Market Operations through innovative ...

SkillsExperience with Cloud services, Infrastructure as Code (IaC) and containerized application developmentFamiliarity with relational databases (e.g., Postgres) and AWS services such as S3, EKS, SageMaker, and BedrockPractical experience with Kubernetes, EKS, Docker, Kafka, MLOps and Large Language Model Operations (LLMOps)Experience working on AIML systems and/or prior ...

with prompt 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.J.P. Morgan is a global leader in financial services, providing strategic advice ...

scalability tradeoff into account.Some skills that will make you stand out: Apache Spark, Iceberg, Kafka, dbtScikit-Learn, XGBoost, PyTorch, MLFlow,, GraphFrames, RayAWS (S3, EMR, SageMaker, Lakeformation), Terraform, Docker, GitHub CI/CDKnowledge Graphs (+ RAG), graph ML, probabilistic programming, A/B testingAdditional InformationFor everyone, everywhere. We're people ...

experience in using one of 3 major cloud technologies (AWS, Azure or GCP) in a production environment, as well as ML platforms (e.g., AWS Sagemaker, Azure Machine Learning studio) Be a ‘lifelong learner’ and can demonstrate a drive to always be learning and developing your skillsets and develop ...

ethicsAn understanding of data safety in use of Large Language ModelsKnowledge and experience of either AWS or Azure:AWS (boto3, Bedrock, Sagemaker, Lambda, S3, EC2)Azure (azure Open AI service, Cosmos DB)PythonLangGraphNeo4j/cypherOther coding languages/frameworks e.g. Java/.NetAI RAG (retrieval augmented generation)Graph RAGFew ...

NumPy, Pandas, Scikit-Learn, xgboost, shap)Advanced working knowledge of SQLHands-on experience with data pipelines and ML infrastructureExperience working within AWS (ideally using Sagemaker) and/or AzureComfort working across our data stack - inc Airflow, SnowflakeExperience with version control and CI/CD practices (ideally using GitHub)Rigorous ...

rankers, or sequence embeddings.You have experience with uplift modelling and conditional average treatment effects for personalisation. You are familiar with dbt, Snowflake, AWS (S3, SageMaker), Airflow, and Trino/data lake stacks.You have prior CRM/marketing/e-commerce ML experience — customer lifecycle segmentation, campaign attribution, contact strategy ...

Cloud-based application development (we use AWS & Azure)Familiarity with one or more ML frameworks and technologies: scikit-learn, xgboost, TensorFlow, PyTorch, Spark, SageMaker, Vertex AI, Kubeflow, Seldon, TritonStrong communication skills, able to express ideas clearly and collaborate across teamsAdditional InformationBring all of you to workWe create the conditions ...

experience across both established enterprise approaches and modern data patterns, including:Cloud-native data platforms (AWS, Azure, GCP).Snowflake, Microsoft Fabric, and/or SageMaker (multi-platform experience advantageous).Data lake and lakehouse architectures.Event-driven and streaming architectures.Data Mesh and/or Data Fabric principles (applied pragmatically, not theoretically ...

ForStrong commercial experience developing machine learning solutions using Python.Experience with frameworks such as:PyTorchTensorFlowScikit-learnXGBoostExperience deploying ML solutions on AWS, including services such as SageMaker, Lambda, and S3.Strong understanding of MLOps tooling, including MLflow, Weights & Biases, or Data Version Control (DVC).Experience developing LLM or Generative AI applications, including … technical stakeholders.Desirable ExperienceAI agents and agentic workflows.Vector databases such as Pinecone, Weaviate, or pgvector.Feature stores including Feast or AWS Feature Store.Docker, Kubernetes, or Amazon ECS.Infrastructure as Code using Terraform or CloudFormation.Big data processing technologies such as Spark or Dask.Experience working within regulated or highly secure environments.What's On OfferWork ...

Amazon, security is central to maintaining customer trust and delivering delightful customer experiences. Our organization is responsible for creating and maintaining a high bar for security across all of Amazon’s products and services. We offer talented security professionals the chance to accelerate their careers with opportunities … stores.The NextGen Security Automation team is looking for a skilled and driven Software Development Engineer (SDE II) to build autonomous security solutions that protect Amazon’s customers. As an SDE II, you will leverage AI/ML technologies to automate detection, analysis, and response across proactive, offensive, and defensive ...

learning solutions using Python. Experience with frameworks such as: PyTorch TensorFlow Scikit-learn XGBoost Experience deploying ML solutions on AWS, including services such as SageMaker, Lambda, and S3. Strong understanding of MLOps tooling, including MLflow, Weights & Biases, or Data Version Control (DVC). Experience developing LLM or Generative … agents and agentic workflows. Vector databases such as Pinecone, Weaviate, or pgvector. Feature stores including Feast or AWS Feature Store. Docker, Kubernetes, or Amazon ECS. Infrastructure as Code using Terraform or CloudFormation. Big data processing technologies such as Spark or Dask. Experience working within regulated or highly secure environments. ...