Amazon Web Services (AWS)
Senior Delivery Consultant - Senior Machine Learning Engineer, AWS Professional
Amazon Web Services (AWS), Seattle, Washington, us, 98127
Overview
Senior Delivery Consultant - Senior Machine Learning Engineer, AWS Professional Services, AWS Professional Services Join to apply for the Senior Delivery Consultant - Senior Machine Learning Engineer, AWS Professional Services, AWS Professional Services role at
Amazon Web Services (AWS) . 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 apply AI/ML to a diverse array of enterprise use cases? Thrilled to be a key part of Amazon, which 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 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 lead customer-focused project teams as a technical leader, and perform hands-on development of ML solutions with exceptional quality. As a Delivery Consultant, you will be proficient in architecting complex, scalable, and secure AI/ML and GenAI solutions tailored to meet the needs of each customer. You\'ll gather requirements, assess current infrastructure, and propose migration strategies to AWS. You will provide guidance on industry trends, emerging technologies, and innovative solutions, and be responsible for leading the implementation process, ensuring 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 with customer teams and the AWS Partner Network (APN) to execute enterprise cloud computing initiatives and deliver focused guidance through global specialty practices across solutions, technologies, and industries. Key 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 AWS
Diverse Experiences: AWS values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job below, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying. Why AWS? Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses. Inclusive Team Culture – Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences inspire us to never stop embracing our uniqueness. Mentorship & Career Growth – We strive to become Earth’s Best Employer by providing mentorship and career development resources. Work/Life Balance – We value work-life harmony and offer flexibility as part of our working culture. 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 5+ years developing predictive modeling, natural language processing, and deep learning, with a proven track record of building and deploying ML models on cloud 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 proficiency in 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 ability 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 (e.g., Airflow, AWS Step Functions). Experience building applications using GenAI technologies (LLMs, Vector Stores, LangChain, Prompt Engineering) Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. If you require a workplace accommodation or adjustment during the application or hiring process, including interview or onboarding support, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. Our compensation reflects the cost of labor across US geographic markets. The base pay ranges from $138,200/year to $239,000/year. Pay is based on location, knowledge, skills, and experience. Amazon is a total compensation company; equity, sign-on and other benefits may be provided as part of a total package. For more information, visit https://www.aboutamazon.com/workplace/employee-benefits. This position will remain posted until filled. Applicants should apply via our internal or external career site. Company – Amazon Web Services, Inc. | Job ID: A3017261
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Senior Delivery Consultant - Senior Machine Learning Engineer, AWS Professional Services, AWS Professional Services Join to apply for the Senior Delivery Consultant - Senior Machine Learning Engineer, AWS Professional Services, AWS Professional Services role at
Amazon Web Services (AWS) . 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 apply AI/ML to a diverse array of enterprise use cases? Thrilled to be a key part of Amazon, which 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 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 lead customer-focused project teams as a technical leader, and perform hands-on development of ML solutions with exceptional quality. As a Delivery Consultant, you will be proficient in architecting complex, scalable, and secure AI/ML and GenAI solutions tailored to meet the needs of each customer. You\'ll gather requirements, assess current infrastructure, and propose migration strategies to AWS. You will provide guidance on industry trends, emerging technologies, and innovative solutions, and be responsible for leading the implementation process, ensuring 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 with customer teams and the AWS Partner Network (APN) to execute enterprise cloud computing initiatives and deliver focused guidance through global specialty practices across solutions, technologies, and industries. Key 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 AWS
Diverse Experiences: AWS values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job below, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying. Why AWS? Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses. Inclusive Team Culture – Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences inspire us to never stop embracing our uniqueness. Mentorship & Career Growth – We strive to become Earth’s Best Employer by providing mentorship and career development resources. Work/Life Balance – We value work-life harmony and offer flexibility as part of our working culture. 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 5+ years developing predictive modeling, natural language processing, and deep learning, with a proven track record of building and deploying ML models on cloud 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 proficiency in 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 ability 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 (e.g., Airflow, AWS Step Functions). Experience building applications using GenAI technologies (LLMs, Vector Stores, LangChain, Prompt Engineering) Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. If you require a workplace accommodation or adjustment during the application or hiring process, including interview or onboarding support, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. Our compensation reflects the cost of labor across US geographic markets. The base pay ranges from $138,200/year to $239,000/year. Pay is based on location, knowledge, skills, and experience. Amazon is a total compensation company; equity, sign-on and other benefits may be provided as part of a total package. For more information, visit https://www.aboutamazon.com/workplace/employee-benefits. This position will remain posted until filled. Applicants should apply via our internal or external career site. Company – Amazon Web Services, Inc. | Job ID: A3017261
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