You will work directly with customers and innovate in a fast-paced organization that contributes to game-changing projects and technologies. You will design and run experiments, research new algorithms, and find new ways of optimizing risk, profitability, and customer experience.We’re looking for Senior Data Scientists capable of using AI/ML and other techniques to design, evangelize, and implement state-of-the-art solutions for never-before-solved problems.Key job responsibilities
As an experienced Senior Data Scientist, you will be responsible for:
1. Lead end-to-end AI/ML and GenAI projects, from understanding business needs to data preparation, model development, solution deployment, and post-production monitoring
2. 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 to address real-world challenges4. Create and deliver best practice recommendations, tutorials, blog posts, publications, sample code, and presentations tailored to technical, business, and executive stakeholders
Diverse Experiences
Amazon values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job description, we encourage 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
Work/Life BalanceMentorship and Career Growth
We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional.
- 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, with attention to detail and ability to convey rigorous technical concepts and considerations to non-experts
- PhD in computer science, machine learning, robotics, operations research, statistics, mathematics or equivalent quantitative field
- AWS experience preferred, with 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 with design, deployment, and evaluation of AI agents and orchestration approaches; experience with open source frameworks like LangChain, LangGraph, LlamaIndex, and/ or similar tools
- 5+ years of deep learning, computer vision, human robotic interaction, algorithms implementation experience using PyTorch or TensorFlow
- Experience in 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 pipelinesPursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.
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