Amazon Web Services (AWS)
Senior Data Scientist, AWS Professional Services
Amazon Web Services (AWS), Dallas, Texas, United States, 75215
Senior Data Scientist, AWS Professional Services
We are seeking a skilled Senior Data Scientist to help customers implement AI/ML solutions and realize transformational business opportunities.
Key Responsibilities
Lead end-to-end AI/ML and GenAI projects, from business needs to data preparation, model development, solution deployment, and post-production monitoring
Collaborate with AI/ML scientists, engineers, and architects to research, design, develop, and evaluate AI algorithms and build ML systems and operations (MLOps) using AWS services
Interact directly with customers to understand business challenges, deliver briefings and deep dive sessions, and guide adoption paths to production
Create and deliver best practice recommendations, tutorials, blog posts, sample code, and presentations tailored to technical, business, and executive stakeholders
Provide customer and market feedback to product and engineering teams to help define product direction
Basic Qualifications
Master's degree in computer science, machine learning, robotics, operations research, statistics, mathematics or equivalent quantitative field with 5+ years of experience; or bachelor's degree with 8+ years of experience
5+ years of building machine learning models for business application experience
3+ years of hands‑on experience with training, fine‑tuning, evaluating, and deploying transformer models in production
Experience with cloud services related to machine learning (e.g., Amazon SageMaker) and generative AI applications
Experience with technical customer‑facing engagements and strong communication skills
Preferred Qualifications
PhD in computer science, machine learning, robotics, operations research, statistics, mathematics or equivalent quantitative field
AWS experience and proficiency in a range of AWS services (e.g., SageMaker, Bedrock, EC2, ECS, EKS, OpenSearch, VPC) and professional certifications (e.g., Solutions Architect Professional)
2+ years of experience designing, deploying, and evaluating AI agents and orchestration approaches; experience with open source frameworks like LangChain, LangGraph, LlamaIndex, or similar tools
5+ years of deep learning, computer vision, human‑robot interaction, algorithms implementation experience using PyTorch or TensorFlow
Experience launching AI applications in production on AWS
Experience building ML pipelines with MLOps best practices, including data preprocessing, distributed & GPU training, model deployment, monitoring, and retraining; experience with container and CI/CD pipelines
About the Team A customer‑facing role with potential travel to customer sites as needed.
Equal Opportunity Employer Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
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Key Responsibilities
Lead end-to-end AI/ML and GenAI projects, from business needs to data preparation, model development, solution deployment, and post-production monitoring
Collaborate with AI/ML scientists, engineers, and architects to research, design, develop, and evaluate AI algorithms and build ML systems and operations (MLOps) using AWS services
Interact directly with customers to understand business challenges, deliver briefings and deep dive sessions, and guide adoption paths to production
Create and deliver best practice recommendations, tutorials, blog posts, sample code, and presentations tailored to technical, business, and executive stakeholders
Provide customer and market feedback to product and engineering teams to help define product direction
Basic Qualifications
Master's degree in computer science, machine learning, robotics, operations research, statistics, mathematics or equivalent quantitative field with 5+ years of experience; or bachelor's degree with 8+ years of experience
5+ years of building machine learning models for business application experience
3+ years of hands‑on experience with training, fine‑tuning, evaluating, and deploying transformer models in production
Experience with cloud services related to machine learning (e.g., Amazon SageMaker) and generative AI applications
Experience with technical customer‑facing engagements and strong communication skills
Preferred Qualifications
PhD in computer science, machine learning, robotics, operations research, statistics, mathematics or equivalent quantitative field
AWS experience and proficiency in a range of AWS services (e.g., SageMaker, Bedrock, EC2, ECS, EKS, OpenSearch, VPC) and professional certifications (e.g., Solutions Architect Professional)
2+ years of experience designing, deploying, and evaluating AI agents and orchestration approaches; experience with open source frameworks like LangChain, LangGraph, LlamaIndex, or similar tools
5+ years of deep learning, computer vision, human‑robot interaction, algorithms implementation experience using PyTorch or TensorFlow
Experience launching AI applications in production on AWS
Experience building ML pipelines with MLOps best practices, including data preprocessing, distributed & GPU training, model deployment, monitoring, and retraining; experience with container and CI/CD pipelines
About the Team A customer‑facing role with potential travel to customer sites as needed.
Equal Opportunity Employer Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
#J-18808-Ljbffr