31 Amazon Sagemaker Jobs - Page 2

Job Summary: We are looking for a skilled AI/ML Developer to join our team, responsible for integrating Amazon Connect with Amazon Lex and Salesforce . The ideal candidate will leverage Amazon Lex to understand and respond to customer queries (such as booking a rental showing), call Salesforce for data processing, and integrate the response back into the customer conversation seamlessly within Amazon Connect. This is a key role for automating and enhancing customer interactions using AI-driven technologies and cloud services. Key Responsibilities: Integration Development & Solution Design: Design and develop intelligent customer service workflows using Amazon Connect and Amazon Lex to handle...

Principle Developer - ML/Prompt Engineer Technologies: Amazon Bedrock, RAG Models, Java, Python, C or C++, AWS Lambda, Responsibilities: Responsible for developing, deploying, and maintaining a Retrieval Augmented Generation (RAG) model in Amazon Bedrock, our cloud-based platform for building and scaling generative AI applications. Design and implement a RAG model that can generate natural language responses, commands, and actions based on user queries and context, using the Anthropic Claude model as the backbone. Integrate the RAG model with Amazon Bedrock, our platform that offers a choice of high-performing foundation models from leading AI companies and Amazon via a single API, along wit...

Role Responsibilities: Build and deploy ML models using Amazon SageMaker Integrate AI/ML solutions with cloud/on-prem pipelines Apply GenAI techniques like neural networks and image processing Ensure production-grade quality in AI solutions Job Requirements: Proven expertise in Amazon SageMaker and ML frameworks Strong programming skills in Python (Java/C++ a plus) Experience with GenAI tools and AI cloud services Understanding of model lifecycle, from training to deployment

Responsibilities : 1. Strategic Leadership : a. Define and drive the overall ML Ops strategy and roadmap for the organization, aligning it with business objectives and technical capabilities. b. Oversee the design, development, and implementation of ML Ops platforms, frameworks, and processes. c. Foster a culture of innovation and continuous improvement within the ML Ops team. 2. Technical Architecture : a. Design and implement scalable, reliable, and efficient ML Ops architectures. b. Select and integrate appropriate tools, technologies, and frameworks to support the ML lifecycle. c. Ensure compliance with industry best practices and standards for ML Ops. 3. Team Management : a. Lead and me...

Role & responsibilities Preferred candidate profile We are seeking a skilled Data Scientist with strong expertise in Python programming and Amazon SageMaker to join our data team. The ideal candidate will have a solid foundation in machine learning, data analysis, and cloud-based model deployment. You will work closely with cross-functional teams to build, deploy, and optimize predictive models and data-driven solutions at scale. Primary Skills Bachelors or Master's degree in Computer Science, Data Science, Statistics, or a related field. 12+ years of experience in data science or machine learning roles. Proficiency in Python and popular ML libraries (e.g., scikit-learn, pandas, NumPy). Hand...

Key Responsibilities: - Lead the design, development, and deployment of machine learning models across various business domains. Architect and implement end-to-end ML pipelines using AWS Sage maker AI, MLflow for experiment tracking, model versioning, and lifecycle management. Oversee model training, tuning, and deployment using Amazon SageMaker AI, including Pipelines, Model Registry, and Model Monitor. Mentor and guide a team of data scientists, ensuring best practices in coding, experimentation, and documentation. Collaborate with engineering, product, and business teams to translate complex problems into data-driven solutions. Establish and enforce MLOps standards for reproducibility, sc...