176 to 200 of 554 Amazon SageMaker Jobs

participation in Kaggle competitions 6-12 months of experience working with RAG pipelines, prompt engineering and/or Generative AI use cases. Experience with SageMaker and/or Vertex AI Return to Work: Have you taken time out for caring responsibilities and are now looking to return to work More ❯

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 Airflow. Proficiency in data pre-processing, data wrangling, and augmentation techniques. Experience with cloud platforms (e.g. AWS, Google Cloud, or Azure) for deploying scalable AI solutions. Understanding of MLOps practices, model deployment, and monitoring in production environments. Experience with Docker, Kubernetes, and CI/CD … 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 More ❯

is hiring for a skilled and proactive Senior Cloud/Platform Engineer to design, build, and support scalable cloud infrastructure and automation pipelines on Amazon Web Services (AWS). You will work closely with DevOps, Security, Data, and AI Application teams to ensure platform reliability, security, and performance. Your … development, staging, and production environments. Automate operational tasks, environment provisioning, and deployments using scripting languages such as Python, Bash, or PowerShell. Enable and maintain Amazon SageMaker environments for scalable ML model training, hosting, and pipelines. Integrate AWS Bedrock to provide foundation model access for generative AI applications, ensuring … Collaborate with security and compliance teams to implement best practices around IAM, encryption, logging, monitoring, and cost optimization. Implement and manage observability tools like Amazon CloudWatch, Prometheus/Grafana, or ELK for monitoring and alerting. Support container orchestration environments using EKS (Kubernetes), ECS, or Fargate. Contribute to incident response More ❯

Experience: 5+ years in cloud-native application development, especially on AWS. Languages & Frameworks: Java, JavaScript, TypeScript, Spring, Spring Boot. AWS Services: Lambda, S3, DynamoDB, SageMaker, SQS, SNS, EventBridge, API Gateway. DevOps Tools: Terraform, Docker, Kubernetes (EKS), GitHub Actions. Other Skills: Agile methodologies, analytical thinking, problem-solving, independent working style More ❯

a strong background in AI research and applied machine learning. Expertise in key data science technologies and techniques, such as Python, Git, AWS, AWS Sagemaker, PyTorch, TensorFlow, Jax, Numpy, Scikit-learn, Time-series forecasting, Classification, Regression, Large-language models, and Experiment Design. Strong stakeholder management skills and the ability More ❯

Experience: 5+ years in cloud-native application development, especially on AWS. Languages & Frameworks: Java, JavaScript, TypeScript, Spring, Spring Boot. AWS Services: Lambda, S3, DynamoDB, SageMaker, SQS, SNS, EventBridge, API Gateway. DevOps Tools: Terraform, Docker, Kubernetes (EKS), GitHub Actions. Other Skills: Agile methodologies, analytical thinking, problem-solving, independent working style More ❯

Experience with social media analytics and user behavior. Knowledge of big data tools like Hadoop, Spark, Kafka. Familiarity with AWS machine learning services like SageMaker and Comprehend. Understanding of data governance and security in AWS. Excellent communication and teamwork skills. Attention to detail and deadline management. Compensation: This is More ❯

platforms on top of an AWS platform and started migration projects for different use cases that are currently implemented in various technologies (SAS, AWS Sagemaker, BW/HANA, etc.). In parallel new use AI cases have to be developed to support business strategy. Job description We are seeking More ❯

Python, with experience in ML libraries such as TensorFlow, PyTorch and Scikit-learn. Experience working with ML training/inference platforms such as Databricks, SageMaker and Seldon. Experience building CI/CD processes with tools such as Jenkins or GitHub Actions. A strong sense of ownership, autonomy and a More ❯

with social media analytics and user behavior analysis. Knowledge of big data technologies like Hadoop, Spark, Kafka. Familiarity with AWS machine learning services like SageMaker and Comprehend. Understanding of data governance and security in AWS. Excellent communication and teamwork skills. Attention to detail and ability to meet deadlines. Compensation More ❯

agentic capabilities using frameworks such as LangChain, CrewAI, AutoGen, and DSPy. AWS Cloud & MLOps: Deploy scalable machine learning workloads on AWS using services like SageMaker, Bedrock, Lambda, S3, DynamoDB, ECS, and EKS. End-to-End AI Product Development : Work across the full ML lifecycle, from data collection and preprocessing More ❯

agentic capabilities using frameworks such as LangChain, CrewAI, AutoGen, and DSPy. AWS Cloud & MLOps: Deploy scalable machine learning workloads on AWS using services like SageMaker, Bedrock, Lambda, S3, DynamoDB, ECS, and EKS. End-to-End AI Product Development : Work across the full ML lifecycle, from data collection and preprocessing More ❯

agentic capabilities using frameworks such as LangChain, CrewAI, AutoGen, and DSPy. AWS Cloud & MLOps: Deploy scalable machine learning workloads on AWS using services like SageMaker, Bedrock, Lambda, S3, DynamoDB, ECS, and EKS. End-to-End AI Product Development : Work across the full ML lifecycle, from data collection and preprocessing More ❯

agentic capabilities using frameworks such as LangChain, CrewAI, AutoGen, and DSPy. AWS Cloud & MLOps: Deploy scalable machine learning workloads on AWS using services like SageMaker, Bedrock, Lambda, S3, DynamoDB, ECS, and EKS. End-to-End AI Product Development : Work across the full ML lifecycle, from data collection and preprocessing More ❯

Transformers. Deep understanding of model deployment and serving technologies (e.g., TensorRT, Triton Inference Server, ONNX, FastAPI). Experience with MLOps tooling (e.g., Kubeflow, MLflow, SageMaker, Vertex AI) and containerization (Docker, Kubernetes). Familiarity with cloud platforms (AWS, GCP, Azure) and deploying AI/ML services in production environments. Strong More ❯

of responsible AI frameworks or security standards (e.g. NIST AI RMF, ISO/IEC 23894). Familiarity with cloud-based ML platforms (e.g. AWS SageMaker, Azure ML, GCP AI Platform). Seniority level Seniority level Mid-Senior level Employment type Employment type Contract Job function Job function Information Technology More ❯

or leveraging Large Language Models (LLMs) via APIs or platform services (e.g., OpenAI, Anthropic, Cohere). ● Familiarity with MLOps tools and practices (e.g., MLflow, SageMaker, Kubeflow). ● Experience in startup or fast-paced environments with rapidly evolving requirements Personal qualities ● Ambitious ● Driven ● Ability to work as part of a More ❯

LangChain, LlamaIndex, LangGraph, CrewAI, AutoGen, or similar. Experience with CI/CD for AI (GenAIOps), model monitoring, and cloud platforms: Google Vertex AI, AWS SageMaker, or Azure AI. Knowledge of AI security, model explainability, and Responsible AI principles. Experience building or integrating voice-enabled chatbots and multi-modal systems. More ❯

LangChain, LlamaIndex, LangGraph, CrewAI, AutoGen, or similar. Experience with CI/CD for AI (GenAIOps), model monitoring, and cloud platforms: Google Vertex AI, AWS SageMaker, or Azure AI. Knowledge of AI security, model explainability, and Responsible AI principles. Experience building or integrating voice-enabled chatbots and multi-modal systems. More ❯

LangChain, LlamaIndex, LangGraph, CrewAI, AutoGen, or similar. Experience with CI/CD for AI (GenAIOps), model monitoring, and cloud platforms: Google Vertex AI, AWS SageMaker, or Azure AI. Knowledge of AI security, model explainability, and Responsible AI principles. Experience building or integrating voice-enabled chatbots and multi-modal systems. More ❯

LangChain, LlamaIndex, LangGraph, CrewAI, AutoGen, or similar. Experience with CI/CD for AI (GenAIOps), model monitoring, and cloud platforms: Google Vertex AI, AWS SageMaker, or Azure AI. Knowledge of AI security, model explainability, and Responsible AI principles. Experience building or integrating voice-enabled chatbots and multi-modal systems. More ❯

LangChain, LlamaIndex, LangGraph, CrewAI, AutoGen, or similar. Experience with CI/CD for AI (GenAIOps), model monitoring, and cloud platforms: Google Vertex AI, AWS SageMaker, or Azure AI. Knowledge of AI security, model explainability, and Responsible AI principles. Experience building or integrating voice-enabled chatbots and multi-modal systems. More ❯

LangChain, LlamaIndex, LangGraph, CrewAI, AutoGen, or similar. Experience with CI/CD for AI (GenAIOps), model monitoring, and cloud platforms: Google Vertex AI, AWS SageMaker, or Azure AI. Knowledge of AI security, model explainability, and Responsible AI principles. Experience building or integrating voice-enabled chatbots and multi-modal systems. More ❯

LangChain, LlamaIndex, LangGraph, CrewAI, AutoGen, or similar. Experience with CI/CD for AI (GenAIOps), model monitoring, and cloud platforms: Google Vertex AI, AWS SageMaker, or Azure AI. Knowledge of AI security, model explainability, and Responsible AI principles. Experience building or integrating voice-enabled chatbots and multi-modal systems. More ❯

LangChain, LlamaIndex, LangGraph, CrewAI, AutoGen, or similar. Experience with CI/CD for AI (GenAIOps), model monitoring, and cloud platforms: Google Vertex AI, AWS SageMaker, or Azure AI. Knowledge of AI security, model explainability, and Responsible AI principles. Experience building or integrating voice-enabled chatbots and multi-modal systems. More ❯