Data Scientist - AWS Professional Services

Are you eager to be at the cutting edge of Machine Learning (ML) and Artificial Intelligence (AI)? Do you want to use AI algorithms to tackle real-world challenges and make a significant impact? The Amazon Web Services Professional Services (ProServe) team is looking for a talented Data Scientist to collaborate with customers in implementing AI/ML solutions and unlock transformative business possibilities. This dynamic team comprises scientists, engineers, and architects who work closely with customers to create customized solutions that leverage the power of AI. You will help clients identify the most valuable use cases for their businesses, select, train, and fine-tune appropriate models, navigate technical and business obstacles, and develop scalable applications that go live in a production environment. Our team also champions best practices to ensure AI is applied responsibly and efficiently. In this role, you will directly interact with clients and innovate within a fast-paced organization that drives groundbreaking projects and technologies. You will design and conduct experiments, research new algorithms, and discover innovative solutions to optimize risk, profitability, and customer experience. We are seeking Data Scientists who can deploy AI/ML and other methodologies to conceive, advocate, and implement cutting-edge solutions for unprecedented challenges. Key Responsibilities: Lead end-to-end AI/ML and GenAI projects, from business needs assessment to data preparation, model development, solution deployment, and post-production monitoring. Collaborate with AI/ML scientists, engineers, and architects to investigate, design, develop, and assess AI algorithms and establish ML operations (MLOps) utilizing AWS services to solve real-world issues. Engage directly with customers to understand their business challenges, deliver detailed briefings and deep-dive sessions, and guide them on effective adoption and production paths. Create and present best practice recommendations, tutorials, blog posts, publications, sample code, and presentations tailored for technical, business, and executive audiences. Communicate customer and market feedback to product and engineering teams to help steer product development. This position is customer-facing and may require occasional travel to customer locations as needed. About AWS: Amazon Web Services (AWS) is the most comprehensive and widely adopted cloud platform worldwide. With ongoing innovation at its core, AWS empowers organizations of all sizes, from startups to Global 500 companies, with its extensive array of products and services. About the Team: We celebrate diversity in experiences and backgrounds. If you feel that you do not meet all the preferred qualifications listed, we encourage you to apply nonetheless. Your non-traditional career path could bring unique insights to our team. Why Join AWS: At AWS, we prioritize work-life balance. We believe that achieving professional success should not compromise personal life. Our culture promotes flexibility to support our employees both at work and at home. We foster an inclusive team environment. Our employee-led affinity groups create a culture that values differing perspectives, underscoring our commitment to diversity and learning. Continuous Learning and Growth: We are focused on talent development and career advancement, ensuring access to mentorship and resources for professional growth. Basic Qualifications: Bachelor's degree or higher in computer science, mathematics, statistics, machine learning or a similar quantitative discipline. A minimum of 3 years of experience building machine learning models for business applications including predictive modeling, natural language processing, and deep learning. A minimum of 3 years of hands-on experience training, fine-tuning, evaluating, and deploying transformer models in production. At least 2 years of experience with cloud services related to machine learning (e.g., Amazon SageMaker) and programming in Python or R, utilizing modern machine learning libraries and tools such as scikit-learn, TensorFlow, and PyTorch. Experience in technical customer-facing roles. Preferred Qualifications: PhD in computer science, machine learning, robotics, operations research, statistics, mathematics or a similar quantitative field. AWS experience is preferred, with knowledge of a variety of AWS services (e.g., SageMaker, Bedrock, EC2, ECS, EKS, OpenSearch) and relevant professional certifications (e.g., Solutions Architect Professional). More than 2 years of experience in designing, deploying, and evaluating AI agents and orchestration approaches, as well as familiarity with open-source frameworks like LangChain, LangGraph, LlamaIndex, or similar tools. At least 5 years of deep learning, computer vision, or human-robotic interaction experience utilizing PyTorch or TensorFlow. Experience launching AI applications in production on AWS. Experience building ML pipelines with MLOps best practices, covering data preprocessing, distributed & GPU training, model deployment, monitoring, and retraining; familiarity with container and CI/CD pipelines. Excellent communication skills, with keen attention to detail and the ability to explain complex technical concepts clearly to non-experts. Amazon is an equal opportunity employer. We embrace diversity and do not discriminate based on protected veteran status, disability, or other legally protected characteristics. Our inclusive culture empowers all Amazonians to deliver optimal results for our customers. If you require any accommodations during the application and hiring process, please reach out for support. Our compensation reflects various US geographic markets, with base pay for this position ranging from $125,500/year to $212,800/year, depending on market location, skills, and experience. Total compensation may also include equity, sign-on payments, and other benefits. For further details on employee benefits, please refer to the Amazon employee benefits page. This role will remain open until filled. Interested candidates are encouraged to apply through our career site.