Senior Delivery Consultant - Senior Machine Learning Engineer, AWS Professional Services

Amazon Web Services (AWS) is a leading cloud platform known for its innovative solutions. They are seeking a Senior Delivery Consultant to help global enterprises implement and manage AI/ML and GenAI solutions, ensuring customer success and adherence to best practices throughout the project lifecycle.

Responsibilities

• Leading project teams and implementing end-to-end AI/ML and GenAI projects, from understanding business needs to data preparation, model development, deployment and monitoring.
• Designing and implementing machine learning pipelines that support high-performance, reliable, scalable, and secure ML workloads.
• Designing scalable ML solutions and operations (MLOps) using AWS services and leveraging GenAI solutions when applicable.
• Collaborating with cross-functional teams (Applied Science, DevOps, Data Engineering, Cloud Infrastructure, Applications) to prepare, analyze, and operationalize data and AI/ML models.
• Serving as a trusted advisor to customers on AI/ML and GenAI solutions and cloud architectures
• Sharing knowledge and best practices within the organization through mentoring, training, publication, and creating reusable artifacts.
• Ensuring solutions meet industry standards and supporting customers in advancing their AI/ML, GenAI, and cloud adoption strategies.

Skills

• 5+ years cloud architecture and implementation
• Bachelor's degree in Computer Science, Engineering, related field, or equivalent experience
• 8+ years leading technical teams and hands-on experience focused on data, software, or ML engineering, with strong understanding of distributed computing. (e.g., data pipelines, training and inference, ML infrastructure design)
• 5+ years developing predictive modeling, natural language processing, and deep learning, with a proven track record of building and deploying ML models on cloud. (e.g., Amazon SageMaker or similar)
• 5+ years developing with SQL, Python, and at least one additional programming language (e.g., Java, Scala, JavaScript, TypeScript). Proficient with leading ML libraries and frameworks (e.g., TensorFlow, PyTorch)
• AWS experience preferred, with proficiency in a range of AWS services (e.g., SageMaker, Bedrock, EC2, ECS, EKS, OpenSearch, Step Functions, VPC, CloudFormation)
• AWS Professional certifications (e.g., Solutions Architect Professional, DevOps Engineer Professional)
• Experience with automation (e.g., Terraform, Python), Infrastructure as Code (e.g., CloudFormation, CDK), and Containers & CI/CD Pipelines.
• Knowledge of common security and compliance standards (e.g., HIPAA, GDPR)
• Strong communication skills with ability to explain complex concepts to technical and non-technical audiences with the ability to lead technical teams in customer projects
• 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 (e.g., MLFlow, Kubeflow) and orchestration (e.g., Airflow, AWS Step Functions). Experience building applications using GenAI technologies (LLMs, Vector Stores, LangChain, Prompt Engineering)

Benefits

• Equity
• Sign-on payments
• Full range of medical, financial, and/or other benefits

Company Overview

• Launched in 2006, Amazon Web Services (AWS) began exposing key infrastructure services to businesses in the form of web services -- now widely known as cloud computing. It was founded in 2002, and is headquartered in Seattle, Washington, USA, with a workforce of 10001+ employees. Its website is http://aws.amazon.com.

Company H1B Sponsorship

• Amazon Web Services (AWS) has a track record of offering H1B sponsorships, with 18969 in 2025, 21175 in 2024, 19057 in 2023, 24088 in 2022, 12233 in 2021, 14881 in 2020. Please note that this does not guarantee sponsorship for this specific role.