Amazon Web Services (AWS)
Senior Delivery Consultant - Senior Machine Learning Engineer, AWS Professional
Amazon Web Services (AWS), Atlanta, Georgia, United States, 30383
Overview
Senior Delivery Consultant - Senior Machine Learning Engineer, AWS Professional Services, AWS Professional Services. Description: Are you excited about building software solutions around large, complex Machine Learning (ML) and Artificial Intelligence (AI) systems? Want to help the largest global enterprises derive business value through the adoption and automation of Generative AI (GenAI)? Excited by using massive amounts of disparate data to develop AI/ML models? Eager to learn to apply AI/ML to a diverse array of enterprise use? Thrilled to be a key part of Amazon, who has been investing in Machine Learning for decades - pioneering and shaping the world’s AI technology? The AWS 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. 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. 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. About the Team / About AWS
Why AWS? Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and continue to innovate — trusted by customers from startups to Global 500 companies. Inclusive Team Culture: AWS fosters inclusion and learning opportunities through affinity groups and ongoing events and learning experiences. Mentorship & Career Growth: We offer knowledge-sharing, mentorship, and career development resources to help you grow. Work/Life Balance: We strive for flexibility to support work-life harmony. 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 with 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 security and compliance standards (e.g., HIPAA, GDPR) Strong communication skills to explain complex concepts to technical and non-technical audiences and lead technical teams in customer projects Experience building ML pipelines with MLOps practices, including data preprocessing, model hosting, feature selection, hyperparameter tuning, distributed & GPU training, deployment, monitoring, and retraining Experience with MLOps tools (e.g., MLFlow, Kubeflow) and orchestration (e.g., Airflow, AWS Step Functions); experience building applications using GenAI technologies (LLMs, Vector Stores, LangChain, Prompt Engineering) Amazon is an equal opportunity employer. If you require a workplace accommodation during the application or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. Job ID: A3017067
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Senior Delivery Consultant - Senior Machine Learning Engineer, AWS Professional Services, AWS Professional Services. Description: Are you excited about building software solutions around large, complex Machine Learning (ML) and Artificial Intelligence (AI) systems? Want to help the largest global enterprises derive business value through the adoption and automation of Generative AI (GenAI)? Excited by using massive amounts of disparate data to develop AI/ML models? Eager to learn to apply AI/ML to a diverse array of enterprise use? Thrilled to be a key part of Amazon, who has been investing in Machine Learning for decades - pioneering and shaping the world’s AI technology? The AWS 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. 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. 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. About the Team / About AWS
Why AWS? Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and continue to innovate — trusted by customers from startups to Global 500 companies. Inclusive Team Culture: AWS fosters inclusion and learning opportunities through affinity groups and ongoing events and learning experiences. Mentorship & Career Growth: We offer knowledge-sharing, mentorship, and career development resources to help you grow. Work/Life Balance: We strive for flexibility to support work-life harmony. 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 with 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 security and compliance standards (e.g., HIPAA, GDPR) Strong communication skills to explain complex concepts to technical and non-technical audiences and lead technical teams in customer projects Experience building ML pipelines with MLOps practices, including data preprocessing, model hosting, feature selection, hyperparameter tuning, distributed & GPU training, deployment, monitoring, and retraining Experience with MLOps tools (e.g., MLFlow, Kubeflow) and orchestration (e.g., Airflow, AWS Step Functions); experience building applications using GenAI technologies (LLMs, Vector Stores, LangChain, Prompt Engineering) Amazon is an equal opportunity employer. If you require a workplace accommodation during the application or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. Job ID: A3017067
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