Senior Delivery Consultant - AI​/ML, AWS Professional Services

Amazon Web Services (AWS) is looking for a skilled ML Engineer to serve as a Delivery Consultant on the Pro Serve team. You will work closely with customers to design, implement, and manage AWS AI/ML and Generative AI solutions that meet their technical and business objectives.

• Lead project teams and implement end-to-end AI/ML and GenAI projects, from business need assessment to data preparation, model development, deployment and monitoring.
• Design and implement machine learning pipelines that support high‑performance, reliable, scalable, and secure ML workloads.
• Design scalable MLOps solutions using AWS services and leverage GenAI when applicable.
• Collaborate with cross‑functional teams (Applied Science, Dev Ops, Data Engineering, Cloud Infrastructure, Applications) to prepare, analyze, and operationalize data and AI/ML models.
• Serve as a trusted advisor to customers on AI/ML and GenAI solutions and cloud architectures.
• Share knowledge and best practices within the organization through mentoring, training, publication, and creating reusable artifacts.
• Ensure solutions meet industry standards and support customers in advancing their AI/ML, GenAI, and cloud adoption strategies.

• Bachelor's degree in business administration, finance, economics, computer science, data science, engineering, or a related field.
• 5+ years of cloud architecture and solution implementation experience.
• 5+ years of development/programming/scripting experience (Python/Java/Bash/Perl).
• 5+ years of leading technical teams and hands‑on experience focused on data, software, or ML engineering, with understanding of distributed computing.
• 5+ years of developing predictive modeling, natural language processing, and deep learning, with experience building and deploying ML models on cloud (e.g., Amazon Sage Maker).

• Experience with the AWS platform, web services, software development, or related technologies.
• Experience conveying complex technical concepts to both technical and business audiences.
• Knowledge of one or more ML frameworks (PyTorch, Tensor Flow) and ML methods including NLP models (BERT, GPT‑2/3), computer vision models, and text‑based models.
• Knowledge of security and compliance standards including HIPAA and GDPR.
• Experience with automation (Terraform, Python), Infrastructure as Code (Cloud Formation, CDK), and Containers & CI/CD Pipelines.
• Experience building ML pipelines with MLOps best practices, including data preprocessing, model hosting, feature selection, hyperparameter tuning, distributed & GPU training, deployment, monitoring, and retraining.
• Experience with MLOps tools (MLFlow, Kubeflow) and orchestration (Airflow, AWS Step Functions). Experience building applications using GenAI technologies (LLMs, Vector Stores, Lang Chain, Prompt Engineering).

Amazon offers comprehensive benefits, including health, vision, and dental insurance, 401(k) matching, paid time off, and parental leave.

United States – California, Mountain View: $176,600–$239,000 annually

United States – California, San Francisco: $176,600–$239,000 annually

United States – Georgia, Atlanta: $153,600–$207,800 annually

United States – Illinois, Chicago: $153,600–$207,800 annually

United States – New Jersey, Jersey City: $169,000–$228,600 annually

United States – New York, New York: $169,000–$228,600 annually

United States – Texas, Dallas: $153,600–$207,800 annually

United States – Virginia, Herndon: $153,600–$207,800 annually

United States – Washington, Seattle: $153,600–$207,800 annually

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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