16 of 16 Permanent Amazon SageMaker Jobs in London

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 ...

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 ...

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 ...

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 ...

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 ...

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. ...

models influence real lending decisions and commercial outcomes Experience deploying and maintaining models within production environments Strong Python, SQL and AWS experience (particularly SageMaker and Lambda) Comfortable working in a fast-moving, hands-on environment with high ownership Excellent communication skills with both technical and business stakeholders What ...

technical standards and reusable patterns. Experience setting technical direction and influencing engineering practices across teams. Hands‐on experience with cloud ML platforms (e.g., AWS SageMaker) and orchestration tools (e.g., Airflow, Step Functions) Strong communication skills and the ability to collaborate across Data Science, Engineering, and Data Platforms. ...

/CD for ML, including automated data validation, model testing, and deployment. Implement ML Engineering solutions using popular MLOps platforms such as AWS Sagemaker , MLflow, Azure ML. End-end custom Sagemaker pipelines for recommendation systemsDesign and implement the engineering components of GAR+RAG systems (e.g., query interpretation and reflection … chunking, embeddings, hybrid retrieval, semantic search), manage prompt libraries, guardrails and structured output for LLMs hosted on Bedrock/SageMaker or self-hostedDesign and implement ML pipelines that utilize Elasticsearch/OpenSearch/Solr, vector DBs, and graph DBs Build evaluation pipelines: offline IR metrics (NDCG ...

dashboards, alerting, and MS Teams integrations—and reduce incidents via telemetry-driven automation and blameless postmortems. Champion AI‐enabled operations using AWS Bedrock/SageMaker and Model Context Protocol (MCP) for log analysis, anomaly detection, incident triage, and workflow orchestration; establish adoption guardrails. Define and enforce cloud guardrails … operations—incident triage, runbooks, and change management—with clear guardrails, auditability, and human-in-the-loop controls. Supporting AI/ML workloads at scale: SageMaker endpoints, GPU node groups, autoscaling, and Kubernetes-based model serving. Policy-as-code (OPA) and compliance implementation across CIS, NIST, ISO 27001, with automated ...

seeking a Principal Customer Success Specialist - Gen AI to transform how organizations plan, execute, and operate their businesses through adoption of Amazon Quick and AWS's generative AI platform. This is a senior individual contributor role within the AWS Specialists & Partners (ASP) Customer Success Center of Excellence, requiring … market impact across hundreds of enterprises globally.Key job responsibilitiesStrategic Customer Transformation- Design and lead comprehensive "business execution" transformation strategies for enterprise customers adopting Amazon Quick and AWS Gen AI services, addressing process redesign, organizational capabilities, change management, and value realization through integrated frameworks and executive alignment.Offering Development & Scaling- Build ...

advanced AI solutions across a wide range of biomedical challenges.Tasks and ResponsibilitiesDesign, maintain and continuously improve AWS-based infrastructure supporting machine learning workloads, including SageMaker, networking, IAM, storage, compute resources and model endpoints.Manage cloud environments through Infrastructure as Code, ensuring consistency, scalability and compliance with enterprise architecture, security … evaluation of new cloud and MLOps technologies.RequirementsHands-on experience designing, implementing and supporting cloud infrastructure in AWS environments.Strong knowledge of AWS services including SageMaker, IAM, networking, storage, compute services and container technologies.Experience with Infrastructure as Code and cloud automation practices.Understanding of cloud security, governance, compliance and access management principles.Experience ...

ownership and delivery responsibility of ML systems (from backend infrastructure through to frontend integration). There is an ongoing migration from MLflow to AWS SageMaker, so you will be working closely with data scientists, engineers and cross-functional stakeholders to deliver this. You will also be responsible for MLOps … Lead, managing teams of 5+, owning end-to-end technical delivery Proficiency with Python and MLflow Strong AWS/cloud-native experience ( ideally with SageMaker exposure) React frontend proficiency Docker, Kafka, and large-scale data systems (e.g. Spark) experience Strong leadership presence and senior stakeholder communication skills ...

ownership and delivery responsibility of ML systems (from backend infrastructure through to frontend integration). There is an ongoing migration from MLflow to AWS SageMaker, so you will be working closely with data scientists, engineers and cross-functional stakeholders to deliver this. You will also be responsible for MLOps … Lead, managing teams of 5+, owning end-to-end technical delivery Proficiency with Python and MLflow Strong AWS/cloud-native experience ( ideally with SageMaker exposure) React frontend proficiency Docker, Kafka, and large-scale data systems (e.g. Spark) experience Strong leadership presence and senior stakeholder communication skills ...