1 to 25 of 75 Amazon SageMaker Jobs

Job ID: Amazon Web Services Australia Pty Ltd Are you a Senior Cloud Architect with GenAI consulting specialist? Do you have real-time Data Analytics, Data Warehousing, Big Data, Modern Data Strategy, Data Lake, Data Engineering and GenAI experience? Do you have senior stakeholder engagement experience to support pre-sales and deliver consulting engagements? Do you like to solve … Vetting Agency clearance (see ). Key job responsibilities Expertise: Collaborate with pre-sales and delivery teams to help partners and customers learn and use services such as AWS Glue, Amazon S3, Amazon DynamoDB, Amazon Relational Database Service (RDS), Amazon Elastic Map Reduce (EMR), Amazon Kinesis, Amazon Redshift, Amazon Athena, AWS Lake Formation, Amazon DataZone, Amazon SageMaker, Amazon Quicksight and Amazon Bedrock. Solutions: Support pre-sales and deliver technical engagements with partners and customers. This includes participating in pre-sales visits, understanding customer requirements, creating consulting proposals and creating packaged data analytics service offerings. Delivery: Engagements include projects proving the use of AWS services to support new distributed computing More ❯

Overview The Amazon Web Services Professional Services (ProServe) team is seeking a skilled Delivery Consultant to join our team at Amazon Web Services (AWS). In this role, you'll work closely with customers to design, implement, and manage AWS solutions that meet their technical requirements and business objectives. You'll be a key player in driving customer … robust and scalable AI solutions for business problems Interact with customers directly to understand the business problem, assist in the implementation of their ML ecosystem Leverage Foundation Models on Amazon Bedrock and Amazon SageMaker to meet performance needs Analyze large historical data to automate and optimize key processes Communicate clearly with attention to detail, translating rigorous mathematical … CV, GNN, or distributed training Ability to create compelling customer proposals and present to executives; proficient English communication in technical and business settings Preferred Qualifications Experience with AWS services (Amazon SageMaker, Amazon Bedrock, EMR, S3, EC2); AWS Certification (Solutions Architect Associate, ML Engineer Associate) preferred Knowledge of AI/ML, generative AI; hands-on prompt engineering and More ❯

Learning Engineer to join the growing data science and AI team. You'll play a key role in designing, developing, and deploying scalable machine learning solutions using Python and Amazon SageMaker . This role is based UK Wide. This role will be Via Umbrella. Working in a Hybrid Model of 1 day a week on site. Key Responsibilities … Design and implement machine learning models for classification, regression, and forecasting tasks. Build and manage end-to-end ML pipelines using Amazon SageMaker . Collaborate with data scientists, engineers, and product teams to integrate ML solutions into production systems. Optimise model performance and scalability. Monitor and maintain deployed models, ensuring reliability and accuracy. Stay up-to-date with … research and tools. Required Skills & Experience Strong proficiency in Python and its ML/data libraries (e.g., NumPy, pandas, scikit-learn, TensorFlow or PyTorch). Hands-on experience with Amazon SageMaker , including training, tuning, and deploying models. Solid understanding of machine learning algorithms and statistical methods. Experience with cloud platforms (AWS preferred). Familiarity with CI/CD More ❯

o Strong understanding of machine learning concepts, algorithms, and best practices. o Proven experience in creating, managing, and deploying ML models using core AWS services such as Amazon SageMaker (for model building, training, and deployment), EC2 (for compute instances), S3 (for data storage), and Lambda (for serverless functions). o Experience with AWS Textract for document data extraction. … seamless data ingestion, transformation, and storage strategies within the AWS ecosystem. o Experience in optimizing AWS resource usage for cost-effectiveness and efficiency in ML operations. o Experience with Amazon Bedrock for leveraging and managing foundation models in generative AI applications. o Knowledge of database services like Amazon RDS or Amazon DynamoDB for storing metadata, features, or More ❯

Delivery Consultant - AI/ML, Professional Services Job ID: AWS EMEA SARL (UK Branch) The Amazon Web Services Professional Services (ProServe) team is seeking a skilled Delivery Consultant to join our team at Amazon Web Services (AWS). In this role, you'll work closely with customers to design, implement, and manage AWS solutions that meet their technical … solutions for business problems Interact with customer directly to understand the business problem, help and aid them in implementation of their ML ecosystem Effectively use Foundation Models available on Amazon Bedrock and Amazon SageMaker to meet our customer's performance needs Analyze and extract relevant information from large amounts of historical data to help automate and optimize … candidates to apply. If your 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's why customers from the most More ❯

Applied Scientist, AWS Professional Services Job ID: Amazon Web Services, Inc. Are you looking to work at the forefront of Machine Learning (ML) and Artificial Intelligence (AI)? Would you be excited to apply AI algorithms to solve real world problems with significant impact? The Amazon Web Services Professional Services (ProServe) team is seeking a skilled Applied Scientist to … candidates to apply. If your 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's why customers from the most … of AI agents and orchestration approaches; experience with open source frameworks like LangChain, LlamaIndex, and/or similar tools Experience building AI applications on AWS using services such as Amazon Bedrock and Amazon SageMaker Experience in patents or publications at top-tier peer-reviewed conferences or journals Strong communication skills, with attention to detail and ability to More ❯

Docker, Kubernetes), and microservices. Experience in integrating AI/ML solutions within cloud environments to ensure scalability, reliability, and security. Familiarity with cloud-based machine learning services like AWS SageMaker, AWS Bedrock, Google AI Platform, Azure Machine Learning & Azure AI Studio Knowledge of MLOps practices for continuous integration and continuous deployment (CI/CD) of machine learning models in More ❯

treasury a plus). Proficiency in Python-including pandas, scikit learn, TensorFlow/PyTorch, LightGBM/XGBoost-and experience with SQL. Hands on experience with cloud ML platforms (AWS SageMaker, Azure ML, or Google AI Platform). Solid understanding of software engineering fundamentals: version control, code reviews, automated testing, and containerization. Familiarity with FX markets, risk management concepts, or More ❯

or commercial projects. Strong programming skills in Python, C++, and Java. Hands-on experience with ML frameworks such as TensorFlow, PyTorch, or JAX. Familiarity with MLOps tools (MLflow, Kubeflow, SageMaker, Vertex AI). Experience with containerization and orchestration (Docker, Kubernetes). Proven ability to deploy and manage workloads in cloud environments (AWS, GCP, Azure). Knowledge of monitoring and More ❯

Applied Scientist, Generative AI Innovation Center Job ID: Amazon Web Services Singapore Private Limited Are you looking to work at the forefront of Machine Learning and AI? Would you be excited to apply Generative AI algorithms to solve real world problems with significant impact? The Generative AI Innovation Center helps AWS customers implement Generative AI solutions and realize transformational … candidates to apply. If your 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's why customers from the most … trl, verl, and for building LLM-powered applications like LangChain, LlamaIndex, and/or similar tools Hands-on experience building generative AI applications on AWS using services such as Amazon Bedrock and Amazon SageMaker Strong communication skills, with attention to detail and ability to convey rigorous technical concepts and considerations to non-experts Our inclusive culture empowers More ❯

Applied Scientist, Generative AI Innovation Center Job ID: Amazon Web Services Singapore Private Limited Are you looking to work at the forefront of Machine Learning and AI? Would you be excited to apply Generative AI algorithms to solve real world problems with significant impact? The Generative AI Innovation Center helps AWS customers implement Generative AI solutions and realize transformational … candidates to apply. If your 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's why customers from the most … trl, verl, and for building LLM-powered applications like LangChain, LlamaIndex, and/or similar tools Hands-on experience building generative AI applications on AWS using services such as Amazon Bedrock and Amazon SageMaker Strong communication skills, with attention to detail and ability to convey rigorous technical concepts and considerations to non-experts Our inclusive culture empowers More ❯

certification desirable). Proven experience deploying and supporting LLMs in production. Strong understanding of LLM fine-tuning (PyTorch, TensorFlow, Hugging Face Trainer, etc.). Experience with ML tooling (e.g. SageMaker, LangChain/LangSmith, MLflow, Dataiku, DataRobot). Knowledge of embeddings, their applications, and limitations. Hands-on experience in Agile/Lean/XP environments. Excellent communication, problem-solving, and More ❯

retrieval techniques (nice to have). - Familiarity with DevOps tooling (Docker, Kubernetes, Terraform) or infrastructure-as-code practices (nice to have). - Exposure to MLOps frameworks (MLflow, DVC, Kubeflow, SageMaker) (nice to have). ECCO Select is committed to hiring and retaining a diverse workforce. Our policy is to provide equal opportunity to all people without regard to race More ❯

Timeout). Desired Qualifications Bachelor s or Master s degree in Computer Science, MIS, or related field. AWS Solutions Architect or Developer certification. Experience with AI/ML platforms (SageMaker, Bedrock, OpenAI, Claude). Knowledge of LLM tuning, Agent-to-Agent protocols, LangGraph, LangSmith. Experience in prompt engineering and generative AI integration. Skills & Tools Programming: Java, Python, Spring Boot More ❯

facing technical role such as Solutions Engineer, Sales Engineer, Developer Advocate, or Technical Consultant. You have deep experience with the AWS ecosystem and services relevant to ML, such as SageMaker, EC2, S3, IAM, and VPC. You are familiar with deep-learning frameworks like PyTorch or JAX, and libraries from the AI ecosystem like Hugging Face Transformers. You have worked More ❯

ML algorithms, plus deep knowledge of LLMs (prompting, fine-tuning, RAG/tool use, evaluation) Hands-on with AWS and Azure services for data/ML (e.g., Bedrock/SageMaker, Azure OpenAI/Azure ML) Strong engineering: Python, APIs, containers, Git; CI/CD (GitHub Actions/Azure DevOps), IaC (Terraform/CloudFormation) Scalable Serving Infrastructure: A containerized, auto More ❯

to support decisions across multiple business areas, including marketing, sales, claims, retention, customer behavior, fraud detection, and customer servicing. Deploy machine learning models into production using AWS services, including SageMaker, S3, Feature Store, ensuring scalable, reliable, and monitored solutions that directly support key business processes. Collaborate with product management and engineering teams to integrate data-driven insights and deploy More ❯

experience with cloud-native development (GCP preferred). Hands-on experience with GCP Vertex AI (model endpoints, pipelines, embeddings, vector search) or equivalent cloud-native ML platforms (e.g. AWS SageMaker, Azure ML) and agent orchestration frameworks such as LangChain and LangGraph Solid understanding of MLOps - CI/CD, IaC (Terraform), experiment tracking, model registry, and monitoring. Proven experience deploying More ❯

and CI/CD pipelines, along with demonstrable experience in the financial services sector. Key Requirements Core Skills and Experience Strong proficiency in AWS-based Machine Learning technologies including SageMaker, Lambda, S3, and EC2. Hands-on experience in CI/CD pipelines and Docker containerisation for ML model development and deployment. Expertise in data preprocessing and feature engineering to More ❯

and CI/CD pipelines, along with demonstrable experience in the financial services sector. Key Requirements Core Skills and Experience Strong proficiency in AWS-based Machine Learning technologies including SageMaker, Lambda, S3, and EC2. Hands-on experience in CI/CD pipelines and Docker containerisation for ML model development and deployment. Expertise in data preprocessing and feature engineering to More ❯

and CI/CD pipelines, along with demonstrable experience in the financial services sector. Key Requirements Core Skills and Experience Strong proficiency in AWS-based Machine Learning technologies including SageMaker, Lambda, S3, and EC2. Hands-on experience in CI/CD pipelines and Docker containerisation for ML model development and deployment. Expertise in data preprocessing and feature engineering to More ❯

and CI/CD pipelines, along with demonstrable experience in the financial services sector. Key Requirements Core Skills and Experience Strong proficiency in AWS-based Machine Learning technologies including SageMaker, Lambda, S3, and EC2. Hands-on experience in CI/CD pipelines and Docker containerisation for ML model development and deployment. Expertise in data preprocessing and feature engineering to More ❯

and managing AI solutions in production environments. Proficiency in AI/ML frameworks and libraries (e.g., TensorFlow, PyTorch, scikit-learn). Experience with cloud-based AI platforms (e.g., AWS SageMaker, Google Cloud AI Platform, Azure Machine Learning). Experience with data management and processing tools (e.g., Hadoop, Spark, SQL). Proficiency in programming languages such as Python and Java. More ❯

intensive applications, including processing unstructured text, integrating with databases (e.g., Pinecone, Weaviate), or handling multimodal inputs like images for OCR-enhanced workflows. Experience with other cloud platforms (e.g., AWS SageMaker, Azure ML) alongside GCP, including containerization with Docker and orchestration via Kubernetes. Contributions to open-source LLM projects, hackathons, or publications showcasing innovative uses of models like GPT-series More ❯

tiny-SD) Frameworks: Python (scikit-learn, pandas, NumPy), Keras, TensorFlow, Pyspark, Streamlit Data Visualization Tools: Matplotlib, Seaborn, Advanced Excel Cloud: S3, Lambda, API Gateway, EC2, Athena, Glue, OpenSearch, Bedrock, SageMaker, Azure Functions, Azure SQL, Azure ML Studio, GCP Vertex AI, GitHub Database: MySQL, Postgres, BigQuery Location: Preferred Sunnyvale/Bay Area; PST time zone coverage required. More ❯