Senior Delivery Consultant - AI/ML, AWS Professional Services

About the role

Amazon Web Services Professional Services (ProServe) is seeking a skilled ML Engineer to join our team as a Delivery Consultant. In this role, you'll work closely with customers to design, implement, and manage AWS AI/ML and GenAI solutions that meet their technical requirements and business objectives. You'll be a key player in driving customer success through their cloud journey, providing technical expertise and best practices throughout the ML project lifecycle.

Key job 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
• This is a customer-facing role with potential travel to customer sites as needed

Basic Qualifications

• Bachelor's degree in Computer Science, Engineering, a related field, or equivalent experience
• 5+ years of cloud architecture and solution implementation experience
• 5+ years of development/programming/scripting language (Python/Java/Bash/Perl) experience
• 5+ years leading technical teams and hands-on experience focused on data, software, or ML engineering, with 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 experience in building and deploying ML models on cloud (e.g., Amazon SageMaker or similar)

Preferred Qualifications

• 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 (e.g., PyTorch, TensorFlow) and ML methods including NLP models (BERT, GPT-2/3), computer vision-based models (object detection, image recognition), and text-based models (Seq2Seq, Topic modeling)
• Knowledge of security and compliance standards including HIPAA and GDPR
• Experience with automation (e.g., Terraform, Python), Infrastructure as Code (e.g., CloudFormation, 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 (e.g., MLFlow, Kubeflow) and orchestration (e.g., Airflow, AWS Step Functions)
• Experience building applications using GenAI technologies (LLMs, Vector Stores, LangChain, Prompt Engineering)

Pay

• USA, CA, Mountain View: $176,600.00 - $239,000.00 USD annually
• USA, CA, San Francisco: $176,600.00 - $239,000.00 USD annually
• USA, GA, Atlanta: $153,600.00 - $207,800.00 USD annually
• USA, IL, Chicago: $153,600.00 - $207,800.00 USD annually
• USA, NJ, Jersey City: $169,000.00 - $228,600.00 USD annually
• USA, NY, New York: $169,000.00 - $228,600.00 USD annually
• USA, TX, Dallas: $153,600.00 - $207,800.00 USD annually
• USA, VA, Herndon: $153,600.00 - $207,800.00 USD annually
• USA, WA, Seattle: $153,600.00 - $207,800.00 USD annually

Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location.

Benefits

• Health insurance (medical, dental, vision, prescription)
• Basic Life & AD&D insurance and option for Supplemental life plans
• EAP, Mental Health Support, Medical Advice Line
• Flexible Spending Accounts
• Adoption and Surrogacy Reimbursement coverage
• 401(k) matching
• Paid time off
• Parental leave

Learn more about our benefits at https://amazon.jobs/en/benefits.

This response is AI-generated, for reference only.