Amazon
Senior Delivery Consultant AI/ML, AWS Professional Services
Amazon, Atlanta, Georgia, United States, 30383
Overview
Senior Delivery Consultant - Senior Machine Learning Engineer, AWS Professional Services . This role focuses on designing, implementing, and managing AWS AI/ML and GenAI solutions for enterprise customers within AWS Professional Services. You will work closely with customers to design, implement, and manage AI/ML and GenAI solutions that meet technical requirements and business objectives. You will lead customer-focused project teams as a technical leader and perform hands-on development of ML solutions with high quality. Travel to customer sites may be required as part of engagements. Location: Atlanta, GA 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 MLOps using AWS services and leveraging GenAI solutions when applicable. Collaborating with cross-functional teams 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. Travel to customer sites as needed.
Basic Qualifications
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)
Preferred Qualifications
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 (Terraform, Python), Infrastructure as Code (CloudFormation, CDK), and Containers & CI/CD Pipelines. Knowledge of common security and compliance standards (HIPAA, GDPR) Strong communication skills with ability to explain complex concepts to technical and non-technical audiences and 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 (Airflow, AWS Step Functions). Experience building applications using GenAI technologies (LLMs, Vector Stores, LangChain, Prompt Engineering)
About AWS
AWS values diverse experiences and encourages you to apply even if you do not meet all preferred qualifications. We value curiosity and inclusion, mentorship, and ongoing career growth. We support work-life balance and flexible working arrangements where possible. Amazon is an equal opportunity employer and does not discriminate on the basis of protected status. If you require accommodations during the application process, please visit AWS accommodations for more information. Location: Atlanta, GA #J-18808-Ljbffr
Senior Delivery Consultant - Senior Machine Learning Engineer, AWS Professional Services . This role focuses on designing, implementing, and managing AWS AI/ML and GenAI solutions for enterprise customers within AWS Professional Services. You will work closely with customers to design, implement, and manage AI/ML and GenAI solutions that meet technical requirements and business objectives. You will lead customer-focused project teams as a technical leader and perform hands-on development of ML solutions with high quality. Travel to customer sites may be required as part of engagements. Location: Atlanta, GA 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 MLOps using AWS services and leveraging GenAI solutions when applicable. Collaborating with cross-functional teams 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. Travel to customer sites as needed.
Basic Qualifications
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)
Preferred Qualifications
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 (Terraform, Python), Infrastructure as Code (CloudFormation, CDK), and Containers & CI/CD Pipelines. Knowledge of common security and compliance standards (HIPAA, GDPR) Strong communication skills with ability to explain complex concepts to technical and non-technical audiences and 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 (Airflow, AWS Step Functions). Experience building applications using GenAI technologies (LLMs, Vector Stores, LangChain, Prompt Engineering)
About AWS
AWS values diverse experiences and encourages you to apply even if you do not meet all preferred qualifications. We value curiosity and inclusion, mentorship, and ongoing career growth. We support work-life balance and flexible working arrangements where possible. Amazon is an equal opportunity employer and does not discriminate on the basis of protected status. If you require accommodations during the application process, please visit AWS accommodations for more information. Location: Atlanta, GA #J-18808-Ljbffr