26 to 39 of 39 Amazon SageMaker Jobs

just experimentation). Cloud platform expertise (AWS strongly preferred; Snowflake a plus) with deep understanding of services for compute, orchestration, storage and ML (e.g., SageMaker, Lambda, ECS/EKS, Step Functions). Experience with MLOps tooling such as: Experiment tracking and model registries (MLflow, Weights & Biases, SageMaker Model … Registry) Workflow orchestration (Airflow, Prefect, Step Functions) Model serving frameworks (SageMaker, TorchServe, TensorFlow Serving, or similar) Feature stores (Feast, Tecton, or custom‐built) Deep understanding of monitoring and observability for ML systems, including operational metrics, data quality checks, drift detection and model performance tracking. CI/CD and Infrastructure ...

skills for querying structured datasets Proven experience developing and validating machine learning models Experience with ML deployment using containerisation or pipeline tools such as SageMaker or similar Strong experience with Git for version control Solid understanding of time series analysis and trend evaluation Excellent exploratory data analysis skills Desirable ...

engineering, model evaluation). Ability to interpret technical designs, data schemas, and integration patterns. Familiarity with cloud-based AI services (e.g., Azure OpenAI, AWS Sagemaker, Databricks, Microsoft Fabric). Delivery & Vendor Engagement Experience working with development teams using agile delivery methodologies. Comfortable coordinating across internal stakeholders, technology teams ...

business application Experience with contextual bandits, off-policy evaluation and learning torank models Experience with AWS technologies such as CDK, Redshift, S3, AWS Glue,Sagemaker, Kinesis, FireHose, Lambda, and IAM roles and permissions. Preferredqualifications: Experience using Unix/Linux Experience in professional software development Experience working within an Agile ...

such as AWS, Azure or GCP across their multiple offerings Familiarity with AI‐specific cloud platform services, such as TogetherAI, ScaleAI, Databricks or AWS SageMaker, at least from a consumer standpoint and strong understanding of underlying technologies Demonstrated understanding of ML model architectures, training dynamics, and optimization techniques Past ...

environment evolves, but typical tools include: Python for experimentation, modelling, and evaluation Weights & Biases (or equivalent) for experiment tracking AWS , including services such as SageMaker and Bedrock Internally supported AI development platforms and tooling This role is not suited to candidates who are dogmatic about specific tools . Adaptability ...

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 ...

model performance, data drift, and system health to ensure reliability and availability. Support ML platforms and infrastructure on-premise or in the cloud (AWS, SageMaker), ensuring scalability and security. Collaborate with data scientists to productionise models and embed ML Ops best practices across the organisation. Ensure governance, compliance, documentation … model maintenance. Hands-on experience with Python (and ML frameworks), containerisation (Docker/Kubernetes), CI/CD pipelines, and cloud ML services (AWS SageMaker preferred). Experience with infrastructure-as-code, production-grade Linux environments, and API services (Flask/Gunicorn). Proficiency in building automated, reliable ML pipelines ...

To get the best candidate experience, please consider applying for a maximum of 3 roles within 12 months to ensure you are not duplicating efforts. Job Category: Sales About Salesforce Salesforce is the #1 AI ...

Azure, and on-premise environments, driving modernisation, scalability, security, and performance.You’ll play a key role in architecting advanced analytics platforms using AWS SageMaker, Azure Machine Learning, and SAS 9.4/Viya, including leading SAS Viya migration and transformation initiatives. Key Responsibilities Lead end-to-end solution architecture across … scalable, secure, and resilient analytics and AI platforms. Drive SAS 9.4 to SAS Viya migration and platform modernisation. Architect machine learning solutions using AWS SageMaker and Azure Machine Learning. Define data platform architecture, analytics pipelines, and enterprise integration patterns. Collaborate with engineering teams to implement CI/ ...

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 ...

physical on-premise datacenters. About the role: Design AI/ML Platforms: Architect scalable end-to-end MLOps and analytics platforms leveraging AWS SageMaker and Azure Machine Learning . Drive Modernisation: Own the strategy and roadmaps for legacy-to-cloud transformations, specifically driving SAS 9.4 to SAS Viya migration … 9.4 and SAS Viya platforms, with direct experience in modernization or migration strategies. AI/ML Lifecycle: Hands-on experience architecting solution platforms with SageMaker and Azure ML. Structured Frameworks: Familiarity with architecture frameworks (TOGAF or equivalent), containerization (Docker/Kubernetes), and API-driven design. £570.00/day Talent ...

ENGINEERING LEAD ESSENTIAL SKILLS Strong commercial experience delivering AI solutions into production Excellent Python engineering skills Experience with Azure AI, Azure ML, Databricks, SageMaker, or similar cloud AI platforms Strong understanding of MLOps, CI/CD, and infrastructure automation Experience with LLMs, agentic frameworks, and modern AI tooling Excellent … client in conjunction with this vacancy only. KEY SKILLS AI Engineering Lead, Machine Learning, Artificial Intelligence, Python, Azure AI, Azure ML, Databricks, SageMaker, Bedrock, MLOps, CI/CD, LLMs, Agentic AI, Cloud Engineering, AI Architecture, Machine Learning Engineering ...

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 ...