1 to 25 of 515 Amazon SageMaker Jobs

Engineering, or a related field 3+ years of experience in machine learning operations, data engineering, or related roles AWS Proficiency: Strong understanding of AWS services (e.g., EC2, S3, Lambda, SageMaker, ECS) and cloud infrastructure management Programming and ML Frameworks: Proficiency in Python and experience with ML frameworks such as scikit-learn, TensorFlow, or PyTorch CI/CD Experience: Experience More ❯

Strong Python skills and experience with AI/ML approaches and frameworks such as RAG, LangChain, TensorFlow, and PyTorch. Exposure to LLMs from model families such as Anthropic, Meta, Amazon, and OpenAI. Familiarity with tools and packages like Pandas, NumPy, scikit-learn, Plotly/Matplotlib, and Jupyter Notebooks. Knowledge of ML-adjacent technologies, including AWS SageMaker and Apache … days ago Edinburgh, Scotland, United Kingdom 3 weeks ago Python and Kubernetes Software Engineer - Data, AI/ML & Analytics Edinburgh, Scotland, United Kingdom 3 months ago Applied Scientist, Amazon Ads - Creative X Edinburgh, Scotland, United Kingdom 3 days ago Edinburgh, Scotland, United Kingdom 3 hours ago Edinburgh, Scotland, United Kingdom 1 month ago Edinburgh, Scotland, United Kingdom 3 weeks More ❯

scikit-learn, Hugging Face, etc.). Strong software engineering background: data structures, algorithms, distributed systems, and version control (Git). Experience designing scalable ML infrastructure on cloud platforms (AWS SageMaker, GCP AI Platform, Azure ML, or equivalent). Solid understanding of data-engineering concepts: SQL/noSQL, data pipelines (Airflow, Prefect, or similar), and batch/streaming frameworks (Spark More ❯

Engineering, or a related field 3+ years of experience in machine learning operations, data engineering, or related roles AWS Proficiency: Strong understanding of AWS services (e.g., EC2, S3, Lambda, SageMaker, ECS) and cloud infrastructure management Programming and ML Frameworks: Proficiency in Python and experience with ML frameworks such as scikit-learn, TensorFlow, or PyTorch CI/CD Experience: Experience More ❯

with data privacy regulations. Technical Competencies The role is a hands-on technical leadership role with advanced experience in at least most of the following technologies Cloud Platforms: AWS (Amazon Web Services): Knowledge of services like S3, EC2, Lambda, RDS, Redshift, EMR, SageMaker, Glue, and Kinesis. Azure: Proficiency in services like Azure Blob Storage, Azure Data Lake, VMs … Kafka, and Apache Flink. ETL Tools: AWS Glue, Azure Data Factory, Talend, and Apache Airflow. AI & Machine Learning: Frameworks: TensorFlow, PyTorch, Scikit-learn, Keras, and MXNet. AI Services: AWS SageMaker, Azure Machine Learning, Google AI Platform. DevOps & Infrastructure as Code: Containerization: Docker and Kubernetes. Infrastructure Automation: Terraform, Ansible, and AWS CloudFormation. API & Microservices: API Development: RESTful API design and … Formation, Azure Purview. Data Security Tools: AWS Key Management Service (KMS), Azure Key Vault. Data Analytics & BI: Visualization Tools: Tableau, Power BI, Looker, and Grafana. Analytics Services: AWS Athena, Amazon QuickSight, Azure Stream Analytics. Development & Collaboration Tools: Version Control: Git (and platforms like GitHub, GitLab). CI/CD Tools: Jenkins, Travis CI, AWS CodePipeline, Azure DevOps. Other Key More ❯

working with various data types: text, image, and video data Familiarity with AI/ML cloud implementations (AWS, Azure, GCP, NVidia) and cloud-based AI/ML services (e.g., Amazon SageMaker, Azure ML) Industry knowledge and experience in one of the following; BFSI, Manufacturing, Retail/Consumer Goods, Healthcare, Energy or Utilities, Tech Extensive experience working with POS More ❯

and maintaining tools that support data science and MLOps/LLMOps workflows. Collaborate with Data Scientists to deploy, serve, and monitor LLMs in real-time and batch environments using Amazon SageMaker , Bedrock Implement Infrastructure-as-Code with AWS CDK , CloudFormation to provision and manage cloud environments. Build and maintain CI/CD pipelines using GitHub Actions , AWS CodePipeline …/MLOps experience with a strong focus on building and delivering scalable infrastructure for ML and AI applications using Python and cloud native technologies Experience with cloud services, especially Amazon Web Services (AWS) - SageMaker, Bedrock, S3, EC2, Lambda, IAM, VPC, ECS/EKS. Proficiency in Infrastructure-as-Code using AWS CDK or CloudFormation . Experience implementing and scaling … MLOps workflows with tools such as MLflow, SageMaker Pipelines . Proven experience building, containerising, and deploying using Docker and Kubernetes . Hands-on experience with CI/CD tools ( GitHub Actions , CodePipeline , Jenkins ) and version control using Git/GitHub . Strong understanding of DevOps concepts including blue/green deployments, canary releases, rollback strategies, and infrastructure automation. Familiarity More ❯

and maintaining tools that support data science and MLOps/LLMOps workflows. Collaborate with Data Scientists to deploy, serve, and monitor LLMs in real-time and batch environments using Amazon SageMaker, Bedrock Implement Infrastructure-as-Code with AWS CDK, CloudFormation to provision and manage cloud environments. Build and maintain CI/CD pipelines using GitHub Actions, AWS CodePipeline …/MLOps experience with a strong focus on building and delivering scalable infrastructure for ML and AI applications using Python and cloud native technologies Experience with cloud services, especially Amazon Web Services (AWS) – SageMaker, Bedrock, S3, EC2, Lambda, IAM, VPC, ECS/EKS. Proficiency in Infrastructure-as-Code using AWS CDK or CloudFormation. Experience implementing and scaling MLOps … workflows with tools such as MLflow, SageMaker Pipelines. Proven experience building, containerising, and deploying using Docker and Kubernetes. Hands-on experience with CI/CD tools (GitHub Actions, CodePipeline, Jenkins) and version control using Git/GitHub. Strong understanding of DevOps concepts including blue/green deployments, canary releases, rollback strategies, and infrastructure automation. Familiarity with security and compliance More ❯

and maintaining tools that support data science and MLOps/LLMOps workflows. Collaborate with Data Scientists to deploy, serve, and monitor LLMs in real-time and batch environments using Amazon SageMaker, Bedrock Implement Infrastructure-as-Code with AWS CDK, CloudFormation to provision and manage cloud environments. Build and maintain CI/CD pipelines using GitHub Actions, AWS CodePipeline …/MLOps experience with a strong focus on building and delivering scalable infrastructure for ML and AI applications using Python and cloud native technologies Experience with cloud services, especially Amazon Web Services (AWS) – SageMaker, Bedrock, S3, EC2, Lambda, IAM, VPC, ECS/EKS. Proficiency in Infrastructure-as-Code using AWS CDK or CloudFormation. Experience implementing and scaling MLOps … workflows with tools such as MLflow, SageMaker Pipelines. Proven experience building, containerising, and deploying using Docker and Kubernetes. Hands-on experience with CI/CD tools (GitHub Actions, CodePipeline, Jenkins) and version control using Git/GitHub. Strong understanding of DevOps concepts including blue/green deployments, canary releases, rollback strategies, and infrastructure automation. Familiarity with security and compliance More ❯

and maintaining tools that support data science and MLOps/LLMOps workflows. Collaborate with Data Scientists to deploy, serve, and monitor LLMs in real-time and batch environments using Amazon SageMaker, Bedrock Implement Infrastructure-as-Code with AWS CDK, CloudFormation to provision and manage cloud environments. Build and maintain CI/CD pipelines using GitHub Actions, AWS CodePipeline …/MLOps experience with a strong focus on building and delivering scalable infrastructure for ML and AI applications using Python and cloud native technologies Experience with cloud services, especially Amazon Web Services (AWS) – SageMaker, Bedrock, S3, EC2, Lambda, IAM, VPC, ECS/EKS. Proficiency in Infrastructure-as-Code using AWS CDK or CloudFormation. Experience implementing and scaling MLOps … workflows with tools such as MLflow, SageMaker Pipelines. Proven experience building, containerising, and deploying using Docker and Kubernetes. Hands-on experience with CI/CD tools (GitHub Actions, CodePipeline, Jenkins) and version control using Git/GitHub. Strong understanding of DevOps concepts including blue/green deployments, canary releases, rollback strategies, and infrastructure automation. Familiarity with security and compliance More ❯

and maintaining tools that support data science and MLOps/LLMOps workflows. Collaborate with Data Scientists to deploy, serve, and monitor LLMs in real-time and batch environments using Amazon SageMaker, Bedrock Implement Infrastructure-as-Code with AWS CDK, CloudFormation to provision and manage cloud environments. Build and maintain CI/CD pipelines using GitHub Actions, AWS CodePipeline …/MLOps experience with a strong focus on building and delivering scalable infrastructure for ML and AI applications using Python and cloud native technologies Experience with cloud services, especially Amazon Web Services (AWS) – SageMaker, Bedrock, S3, EC2, Lambda, IAM, VPC, ECS/EKS. Proficiency in Infrastructure-as-Code using AWS CDK or CloudFormation. Experience implementing and scaling MLOps … workflows with tools such as MLflow, SageMaker Pipelines. Proven experience building, containerising, and deploying using Docker and Kubernetes. Hands-on experience with CI/CD tools (GitHub Actions, CodePipeline, Jenkins) and version control using Git/GitHub. Strong understanding of DevOps concepts including blue/green deployments, canary releases, rollback strategies, and infrastructure automation. Familiarity with security and compliance More ❯

and maintaining tools that support data science and MLOps/LLMOps workflows. Collaborate with Data Scientists to deploy, serve, and monitor LLMs in real-time and batch environments using Amazon SageMaker, Bedrock Implement Infrastructure-as-Code with AWS CDK, CloudFormation to provision and manage cloud environments. Build and maintain CI/CD pipelines using GitHub Actions, AWS CodePipeline …/MLOps experience with a strong focus on building and delivering scalable infrastructure for ML and AI applications using Python and cloud native technologies Experience with cloud services, especially Amazon Web Services (AWS) – SageMaker, Bedrock, S3, EC2, Lambda, IAM, VPC, ECS/EKS. Proficiency in Infrastructure-as-Code using AWS CDK or CloudFormation. Experience implementing and scaling MLOps … workflows with tools such as MLflow, SageMaker Pipelines. Proven experience building, containerising, and deploying using Docker and Kubernetes. Hands-on experience with CI/CD tools (GitHub Actions, CodePipeline, Jenkins) and version control using Git/GitHub. Strong understanding of DevOps concepts including blue/green deployments, canary releases, rollback strategies, and infrastructure automation. Familiarity with security and compliance More ❯

Data Science, MLOps, and LLMOps workflows across the organisation. Drive strategy and execution for deploying, serving, and monitoring large language models (LLMs) in real-time and batch environments using Amazon SageMaker, Bedrock, and related services. Guide the use of Infrastructure-as-Code (IaC) practices with AWS CDK and CloudFormation to provision and manage secure and maintainable cloud environments. … experience in DevOps/MLOps roles with demonstrated impact in building, scaling, and securing ML/AI infrastructure in cloud-native environments. Strong experience with AWS services such as SageMaker, Bedrock, S3, EC2, Lambda, IAM, VPC, ECS/EKS, with a strong command of cloud solution architecture. Advanced proficiency in Infrastructure-as-Code practices using AWS CDK, CloudFormation, or … Terraform in production environments. Proven track record designing and operationalised end-to-end MLOps pipelines with tools such as MLflow, SageMaker Pipelines, or equivalent frameworks. Extensive experience building and operating containerised applications using Docker and Kubernetes, including production-grade orchestration and monitoring. Deep experience with CI/CD best practices with hands-on expertise in GitHub Actions, Jenkins, and More ❯

Data Science, MLOps, and LLMOps workflows across the organisation. Drive strategy and execution for deploying, serving, and monitoring large language models (LLMs) in real-time and batch environments using Amazon SageMaker, Bedrock, and related services. Guide the use of Infrastructure-as-Code (IaC) practices with AWS CDK and CloudFormation to provision and manage secure and maintainable cloud environments. … experience in DevOps/MLOps roles with demonstrated impact in building, scaling, and securing ML/AI infrastructure in cloud-native environments. Strong experience with AWS services such as SageMaker, Bedrock, S3, EC2, Lambda, IAM, VPC, ECS/EKS, with a strong command of cloud solution architecture. Advanced proficiency in Infrastructure-as-Code practices using AWS CDK, CloudFormation, or … Terraform in production environments. Proven track record designing and operationalised end-to-end MLOps pipelines with tools such as MLflow, SageMaker Pipelines, or equivalent frameworks. Extensive experience building and operating containerised applications using Docker and Kubernetes, including production-grade orchestration and monitoring. Deep experience with CI/CD best practices with hands-on expertise in GitHub Actions, Jenkins, and More ❯

Data Science, MLOps, and LLMOps workflows across the organisation. Drive strategy and execution for deploying, serving, and monitoring large language models (LLMs) in real-time and batch environments using Amazon SageMaker, Bedrock, and related services. Guide the use of Infrastructure-as-Code (IaC) practices with AWS CDK and CloudFormation to provision and manage secure and maintainable cloud environments. … experience in DevOps/MLOps roles with demonstrated impact in building, scaling, and securing ML/AI infrastructure in cloud-native environments. Strong experience with AWS services such as SageMaker, Bedrock, S3, EC2, Lambda, IAM, VPC, ECS/EKS, with a strong command of cloud solution architecture. Advanced proficiency in Infrastructure-as-Code practices using AWS CDK, CloudFormation, or … Terraform in production environments. Proven track record designing and operationalised end-to-end MLOps pipelines with tools such as MLflow, SageMaker Pipelines, or equivalent frameworks. Extensive experience building and operating containerised applications using Docker and Kubernetes, including production-grade orchestration and monitoring. Deep experience with CI/CD best practices with hands-on expertise in GitHub Actions, Jenkins, and More ❯

Data Science, MLOps, and LLMOps workflows across the organisation. Drive strategy and execution for deploying, serving, and monitoring large language models (LLMs) in real-time and batch environments using Amazon SageMaker, Bedrock, and related services. Guide the use of Infrastructure-as-Code (IaC) practices with AWS CDK and CloudFormation to provision and manage secure and maintainable cloud environments. … experience in DevOps/MLOps roles with demonstrated impact in building, scaling, and securing ML/AI infrastructure in cloud-native environments. Strong experience with AWS services such as SageMaker, Bedrock, S3, EC2, Lambda, IAM, VPC, ECS/EKS, with a strong command of cloud solution architecture. Advanced proficiency in Infrastructure-as-Code practices using AWS CDK, CloudFormation, or … Terraform in production environments. Proven track record designing and operationalised end-to-end MLOps pipelines with tools such as MLflow, SageMaker Pipelines, or equivalent frameworks. Extensive experience building and operating containerised applications using Docker and Kubernetes, including production-grade orchestration and monitoring. Deep experience with CI/CD best practices with hands-on expertise in GitHub Actions, Jenkins, and More ❯

Data Science, MLOps, and LLMOps workflows across the organisation. Drive strategy and execution for deploying, serving, and monitoring large language models (LLMs) in real-time and batch environments using Amazon SageMaker, Bedrock, and related services. Guide the use of Infrastructure-as-Code (IaC) practices with AWS CDK and CloudFormation to provision and manage secure and maintainable cloud environments. … experience in DevOps/MLOps roles with demonstrated impact in building, scaling, and securing ML/AI infrastructure in cloud-native environments. Strong experience with AWS services such as SageMaker, Bedrock, S3, EC2, Lambda, IAM, VPC, ECS/EKS, with a strong command of cloud solution architecture. Advanced proficiency in Infrastructure-as-Code practices using AWS CDK, CloudFormation, or … Terraform in production environments. Proven track record designing and operationalised end-to-end MLOps pipelines with tools such as MLflow, SageMaker Pipelines, or equivalent frameworks. Extensive experience building and operating containerised applications using Docker and Kubernetes, including production-grade orchestration and monitoring. Deep experience with CI/CD best practices with hands-on expertise in GitHub Actions, Jenkins, and More ❯

Data Science, MLOps, and LLMOps workflows across the organisation. Drive strategy and execution for deploying, serving, and monitoring large language models (LLMs) in real-time and batch environments using Amazon SageMaker, Bedrock, and related services. Guide the use of Infrastructure-as-Code (IaC) practices with AWS CDK and CloudFormation to provision and manage secure and maintainable cloud environments. … experience in DevOps/MLOps roles with demonstrated impact in building, scaling, and securing ML/AI infrastructure in cloud-native environments. Strong experience with AWS services such as SageMaker, Bedrock, S3, EC2, Lambda, IAM, VPC, ECS/EKS, with a strong command of cloud solution architecture. Advanced proficiency in Infrastructure-as-Code practices using AWS CDK, CloudFormation, or … Terraform in production environments. Proven track record designing and operationalised end-to-end MLOps pipelines with tools such as MLflow, SageMaker Pipelines, or equivalent frameworks. Extensive experience building and operating containerised applications using Docker and Kubernetes, including production-grade orchestration and monitoring. Deep experience with CI/CD best practices with hands-on expertise in GitHub Actions, Jenkins, and More ❯

computing, both on-premises and on cloud platforms, and experience in building end-to-end scalable ML infrastructure with on-premise DGX or cloud platforms including AWS EKS/SageMaker, Azure Machine Learning/AKS, or common ML platforms (ClearML, MLflow, Weights and Biases). Cloud & Automation: Strong understanding of AWS, Azure, containerization/Kubernetes, multiple automation/DevOps More ❯

About Apexon: Apexon brings together distinct core competencies – in AI, analytics, app development, cloud, commerce, CX, data, DevOps, IoT, mobile, quality engineering and UX, and our deep expertise in BFSI, healthcare, and life sciences – to help businesses capitalize on the More ❯

About Apexon: Apexon brings together distinct core competencies – in AI, analytics, app development, cloud, commerce, CX, data, DevOps, IoT, mobile, quality engineering and UX, and our deep expertise in BFSI, healthcare, and life sciences – to help businesses capitalize on the More ❯

About Apexon: Apexon brings together distinct core competencies – in AI, analytics, app development, cloud, commerce, CX, data, DevOps, IoT, mobile, quality engineering and UX, and our deep expertise in BFSI, healthcare, and life sciences – to help businesses capitalize on the More ❯

About Apexon: Apexon brings together distinct core competencies – in AI, analytics, app development, cloud, commerce, CX, data, DevOps, IoT, mobile, quality engineering and UX, and our deep expertise in BFSI, healthcare, and life sciences – to help businesses capitalize on the More ❯

for data insights Data Bricks/Data QISQL for data access and processing (PostgreSQL preferred, but general SQL knowledge is important) Latest Data Science platforms (e.g., Databricks, Dataiku, AzureML, SageMaker) and frameworks (e.g., TensorFlow, MXNet, scikit-learn) Software engineering practices (coding standards, unit testing, version control, code review) Hadoop distributions (Cloudera, Hortonworks), NoSQL databases (Neo4j, Elastic), streaming technologies (Spark More ❯

with Single Sign-On/OIDC integration and a deep understanding of OAuth, JWT/JWE/JWS. Solid understanding of backend performance optimization and debugging. Knowledge of AWS SageMaker and data analytics tools. Proficiency in frameworks TensorFlow, PyTorch, or similar. Preferred Qualifications, Capabilities, and Skills: Familiarity with LangChain, Langgraph, or any Agentic Frameworks is a strong plus. Python More ❯