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.

You will lead customer-focused project teams as a technical leader, and perform hands-on development of ML solutions with exceptional quality. 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. You'll work closely with stakeholders to gather requirements, assess current infrastructure, and propose effective migration strategies to AWS. As trusted advisors to our customers, providing guidance on industry trends, emerging technologies, and innovative solutions, you will be responsible for leading the implementation process, ensuring adherence to best practices, optimizing performance, and managing risks throughout the project.

The AWS Professional Services organization is a global team of experts that help customers realize their desired business outcomes when using the AWS Cloud. We work together with customer teams and the AWS Partner Network (APN) to execute enterprise cloud computing initiatives. Our team provides assistance through a collection of offerings which help customers achieve specific outcomes related to enterprise cloud adoption. We also deliver focused guidance through our global specialty practices, which cover a variety of solutions, technologies, and industries.

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

Benefits

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

This response is AI-generated, for reference only.