Amazon Web Services (AWS)
Senior Delivery Consultant - Senior Machine Learning Engineer, AWS Professional
Amazon Web Services (AWS), Seattle, Washington, us, 98127
Senior Delivery Consultant - Senior Machine Learning Engineer, AWS Professional Services
Join to apply for the
Senior Delivery Consultant - Senior Machine Learning Engineer, AWS Professional Services
role at
Amazon Web Services (AWS) Get AI-powered advice on this job and more exclusive features. 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 AWS. In this role, you will work closely with customers to design, implement, and manage AWS AI/ML and GenAI solutions that meet their 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. You will architect complex, scalable, and secure AI/ML and GenAI solutions tailored to meet the specific needs of each customer, 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 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, delivering offerings across enterprise cloud adoption and focused guidance through global specialty practices. 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 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 AWS values diverse experiences and encourages candidates to apply even if not meeting all preferred qualifications. AWS is the world’s most comprehensive and broadly adopted cloud platform, with a culture focused on inclusion, mentorship, work-life balance, and career growth. 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 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 (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 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. Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you need workplace accommodations, visit amazon.jobs accommodations for more information. Our compensation reflects the cost of labor across US geographic markets. This position will remain posted until filled. Applicants should apply via our career site. Company
- Amazon Web Services, Inc. Job ID: A3041017
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Join to apply for the
Senior Delivery Consultant - Senior Machine Learning Engineer, AWS Professional Services
role at
Amazon Web Services (AWS) Get AI-powered advice on this job and more exclusive features. 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 AWS. In this role, you will work closely with customers to design, implement, and manage AWS AI/ML and GenAI solutions that meet their 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. You will architect complex, scalable, and secure AI/ML and GenAI solutions tailored to meet the specific needs of each customer, 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 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, delivering offerings across enterprise cloud adoption and focused guidance through global specialty practices. 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 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 AWS values diverse experiences and encourages candidates to apply even if not meeting all preferred qualifications. AWS is the world’s most comprehensive and broadly adopted cloud platform, with a culture focused on inclusion, mentorship, work-life balance, and career growth. 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 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 (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 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. Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you need workplace accommodations, visit amazon.jobs accommodations for more information. Our compensation reflects the cost of labor across US geographic markets. This position will remain posted until filled. Applicants should apply via our career site. Company
- Amazon Web Services, Inc. Job ID: A3041017
#J-18808-Ljbffr