Senior Delivery Consultant - AI/ML, AWS Professional Services

About the role

The Amazon Web Services Professional Services (ProServe) team is seeking a skilled ML Engineer to join our team as a Delivery Consultant at Amazon Web Services (AWS). 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. You will lead customer-focused project teams as a technical leader, and perform hands-on development of ML solutions with exceptional quality.

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

Requirements

• Possessing a deep understanding of AWS products and services, as a Delivery Consultant you will be proficient in architecting complex, scalable, and secure AI/ML and GenAI solutions tailored to meet the specific needs of each customer.
• Working closely with stakeholders to gather requirements, assess current infrastructure, and propose effective migration strategies to AWS.

Qualifications

• Bachelor's degree in business administration, finance, economics, computer science, data science, engineering, or other related field
• 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)

Skills

• 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)

Benefits

Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including 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, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits.

Pay

Base salary range for this position is listed below. Final compensation will be determined based on factors including experience, qualifications, and location.

• 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

Schedule

Work/Life Balance: We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud.