201 to 225 of 241 Permanent Amazon SageMaker Jobs

with AWS technical teams Technical focus You will bring experience across several of the following areas: Generative AI and machine learning, including Bedrock and SageMaker Data and analytics, including Amazon Marketing Cloud and Clean Rooms Customer experience platforms such as Personalize and Connect Modern application development using Lambda … have Advanced AWS certifications, such as AWS Solutions Architect Professional or Specialty certifications in Machine Learning, Data Analytics or Security. Hands‐on experience with Amazon Bedrock, generative AI implementations or broader AI use cases. Familiarity with Amazon Marketing Cloud, advertising technology or marketing technology environments. Previous experience working ...

improving the core infrastructure that powers Evoke’s AI and Machine Learning platforms* Developing expertise in AWS AI technologies, including services such as Amazon Bedrock and SageMaker* Providing technical support and operational ownership for Evoke’s core AI platforms and services* Contributing to platform reliability, observability, automation … experience in a similar Cloud, Platform, or Infrastructure Engineering role* Strong expertise in AWS cloud technologies, including AI and Machine Learning services such as Amazon Bedrock and SageMaker* Solid understanding of Agentic AI concepts and supporting technologies, including platforms such as AWS AgentCore* Strong knowledge of Kubernetes ...

modernization. Engineer the Value – Co-Innovation & Delivery Launch Ecosystem Lighthouses: Lead the deployment of first-of-their-kind solutions using Vertex AI (GCP) or Amazon Bedrock/SageMaker (AWS); embed agentic loops into enterprise workflows within 90 days. Build the Enablement Engine: Stand up the programs—certifications, playbooks … Converts deep-tech architectures into board-level narratives that unlock seven-figure budgets. Tech Superpowers AI-Native Architect Liaison: Translates Vertex AI (GCP) or Amazon Bedrock/SageMaker (AWS) features into monetizable, agentic solutions that solve complex business frictions. Distributed-Data Fluent: Designs BigQuery (GCP) or Redshift ...

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 ...

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 ...

solutions across a wide range of biomedical challenges. Tasks and Responsibilities Design, 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 … cloud and MLOps technologies. Requirements Hands-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 ...

integration Lead architectural decisions across the ML stack, ensuring scalability, reliability, and alignment with business goals Drive the ongoing migration from MLflow to AWS SageMaker, maintaining continuity and minimising disruption Define and enforce MLOps best practices across model training, serving, monitoring, and deployment MLOps & Engineering Design and maintain scalable … data engineering, and large-scale data processing Experience with containerisation (Docker) and scalable data systems (e.g. Spark, Kafka) Nice-to-Have Experience with AWS SageMaker or similar managed ML platforms Background in safety-critical or regulated industries (aerospace, aviation, or similar) Familiarity with Kafka or event-driven architectures ...

while creating measurable business value for its clients. Base Location: London, UK Role Overview Build PoCs, MVPs, and customer demonstrations Develop GenAI applications using Amazon Bedrock and AWS AI services Design and implement production-grade AI solutions on AWS Lead customer workshops and architecture discussions Guide engineering teams through … Skills & Experience 10+ years of experience in cloud architecture and solution design. Proven experience with AWS AI/ML services such as Agent Core, Amazon Bedrock, SageMaker, Comprehend, Textract, and GenAI patterns (RAG, copilots, agents). Experience in application modernization, cloud migration, DevSecOps, and Infrastructure as Code. Nice ...

extending lives in areas of high unmet medical need. Задачи Design, 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 while ensuring consistency, scalability and compliance with enterprise architecture, security … cloud and MLOps technologies Требования Hands-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 ...

projects on AWS, including Landing Zone deployments, migrations and modernization work. Your focus is AI/ML delivery on AWS using Bedrock, SageMaker and Terraform, building production-grade data pipelines, evaluation frameworks and MLOps, while contributing to broader AWS engagements as needed. #J-18808-Ljbffr ...

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 … with a wide range of stakeholders, including colleagues and leadership - Bachelor's degree, or Master's degree - Experience with AWS AI/ML services (SageMaker, Bedrock, Q for Business, Q for Dev etc.) - Experience in consulting or working for large, complex organizations Amazon est un employeur engagé pour ...

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 … with a wide range of stakeholders, including peers and leadership - Bachelor's degree, or Master's degree - Experience with AWS AI/ML services (SageMaker, Bedrock, Q for Business, Q for Dev etc.) - Experience in consulting or working for large, complex organizations Amazon est un employeur engagé pour ...

development programme that will allow you the freedom to take on training and certifications on the training platform of your choice. As an Amazon Web Services (AWS) cloud architect, you'll assist in implementing and supporting large-scale cloud implementations on Amazon AWS. Other duties include architecting … . Deep understanding of AI/ML solution patterns (data pipelines, training, inference, monitoring, and MLOps) and how they map onto AWS services (e.g. SageMaker, Batch, Step Functions, EKS/ECS, data lake components). Proven ability to take research and prototype environments to enterprise-ready architectures, balancing speed ...

development programme that will allow you the freedom to take on training and certifications on the training platform of your choice. As an Amazon Web Services (AWS) cloud architect, you'll assist in implementing and supporting large-scale cloud implementations on Amazon AWS. Other duties include architecting … . Deep understanding of AI/ML solution patterns (data pipelines, training, inference, monitoring, and MLOps) and how they map onto AWS services (e.g. SageMaker, Batch, Step Functions, EKS/ECS, data lake components). Proven ability to take research and prototype environments to enterprise-ready architectures, balancing speed ...

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 ...

generation and business KPIs.Prioritize initiatives that directly improve LTV, retention, ARPU, ROAS, and operational efficiency.Deliver robust, production-ready ML systems across multiple verticals.Leverage AWS SageMaker, Snowflake, and internal tools with strong MLOps practices.Build and manage a high-performing AI/ML team of 10–20 professionals.Promote a culture … presence with strong stakeholder communication skills across technical and non-technical audiences.Hands-on experience with user-level and performance marketing data.• Proficiency with AWS (SageMaker, Lambda, Step Functions), Snowflake, and modern MLOps tooling.Familiarity with ML frameworks including PyTorch, TensorFlow, scikit-learn, and XGBoost.Experience managing and scaling high-performing data ...

KPIs. Prioritize initiatives that directly improve LTV, retention, ARPU, ROAS, and operational efficiency. Deliver robust, production-ready ML systems across multiple verticals. Leverage AWS SageMaker, Snowflake, and internal tools with strong MLOps practices. Build and manage a high-performing AI/ML team of 10–20 professionals. Promote … with strong stakeholder communication skills across technical and non-technical audiences. Hands-on experience with user-level and performance marketing data.• Proficiency with AWS (SageMaker, Lambda, Step Functions), Snowflake, and modern MLOps tooling. Familiarity with ML frameworks including PyTorch, TensorFlow, scikit-learn, and XGBoost. Experience managing and scaling high ...

manage what already exists. The team is small but technically strong - production ML in fraud detection, text moderation, and taxonomy classification, running on SageMaker with a dbt/Snowflake stack. We're operating reactively, and there's significantly more value data science can unlock across the marketplace.You'll have … years in data science or ML engineering, with 3+ years directly managing data science teamsNice-to-HavesMarketplace, SaaS, or fintech experienceFamiliarity with our stack (SageMaker, Snowflake, dbt, Docker)Built or contributed to experimentation platforms or MLOps infrastructureWhy This RoleReal data, real scale. Millions of transactions monthly across 120+ countries ...

technologies, modern architecture patterns and industry best practices Connect to your skills and professional experience AWS Expertise Proven experience designing and architecting solutions on Amazon Web Services (AWS). Strong understanding of AWS services including compute, storage, networking, security, data, analytics, integration and serverless technologies. Experience developing cloud transformation … influence architectural decisions and drive alignment across multiple stakeholder groups. Emerging Technologies Understanding of AWS AI/ML and Generative AI services, including Amazon Bedrock and SageMaker. Knowledge of modern data platforms, analytics solutions and cloud-native architectures. Interest in emerging technologies and their application to business transformation challenges. ...

development programme that will allow you the freedom to take on training and certifications on the training platform of your choice. As an Amazon Web Services (AWS) cloud architect, you'll assist in implementing and supporting large-scale cloud implementations on Amazon AWS. Other duties include architecting … depth).Deep understanding of AI/ML solution patterns (data pipelines, training, inference, monitoring, and MLOps) and how they map onto AWS services (e.g. SageMaker, Batch, Step Functions, EKS/ECS, data lake components).Proven ability to take research and prototype environments to enterprise‐ready architectures, balancing speed, robustness ...

development programme that will allow you the freedom to take on training and certifications on the training platform of your choice. As an Amazon Web Services (AWS) cloud architect, you'll assist in implementing and supporting large-scale cloud implementations on Amazon AWS. Other duties include architecting … depth).Deep understanding of AI/ML solution patterns (data pipelines, training, inference, monitoring, and MLOps) and how they map onto AWS services (e.g. SageMaker, Batch, Step Functions, EKS/ECS, data lake components).Proven ability to take research and prototype environments to enterprise‐ready architectures, balancing speed, robustness ...

development programme that will allow you the freedom to take on training and certifications on the training platform of your choice. As an Amazon Web Services (AWS) cloud architect, you'll assist in implementing and supporting large-scale cloud implementations on Amazon AWS. Other duties include architecting … depth).Deep understanding of AI/ML solution patterns (data pipelines, training, inference, monitoring, and MLOps) and how they map onto AWS services (e.g. SageMaker, Batch, Step Functions, EKS/ECS, data lake components).Proven ability to take research and prototype environments to enterprise‐ready architectures, balancing speed, robustness ...

development programme that will allow you the freedom to take on training and certifications on the training platform of your choice. As an Amazon Web Services (AWS) cloud architect, you'll assist in implementing and supporting large-scale cloud implementations on Amazon AWS. Other duties include architecting … depth).Deep understanding of AI/ML solution patterns (data pipelines, training, inference, monitoring, and MLOps) and how they map onto AWS services (e.g. SageMaker, Batch, Step Functions, EKS/ECS, data lake components).Proven ability to take research and prototype environments to enterprise‐ready architectures, balancing speed, robustness ...

development programme that will allow you the freedom to take on training and certifications on the training platform of your choice. As an Amazon Web Services (AWS) cloud architect, you'll assist in implementing and supporting large-scale cloud implementations on Amazon AWS. Other duties include architecting … depth).Deep understanding of AI/ML solution patterns (data pipelines, training, inference, monitoring, and MLOps) and how they map onto AWS services (e.g. SageMaker, Batch, Step Functions, EKS/ECS, data lake components).Proven ability to take research and prototype environments to enterprise‐ready architectures, balancing speed, robustness ...