Amazon Web Services (AWS)
Senior Delivery Consultant AI/ML, AWS Professional Services
Amazon Web Services (AWS), Austin, Texas, us, 78716
Overview
Are you excited about building software solutions around large, complex Machine Learning (ML) and Artificial Intelligence (AI) systems? You will join the AWS Professional Services team to design, implement, and manage AI/ML and GenAI solutions that meet customers’ 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. 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 the team
The AWS Professional Services organization is a global team of experts that helps 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 our global specialty practices. 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 for explaining 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 (data preprocessing, model hosting, feature selection, hyperparameter tuning, distributed & GPU training, deployment, monitoring, 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 and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you need a workplace accommodation during the application and hiring process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner. Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $138,200/year in our lowest geographic market up to $239,000/year in our highest geographic market. Pay is based on factors including market location and job-related knowledge, skills, and experience. This position may include equity, sign-on payments, and other components as part of a total compensation package. For more information, please 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. Job ID: A3041017 Seniority level
Mid-Senior level Employment type
Full-time Job function
Research, Science, and Engineering Industries IT Services and IT Consulting Our goal is to ensure applicants are informed and able to apply. This description contains the essential aspects of the role and responsibilities.
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Are you excited about building software solutions around large, complex Machine Learning (ML) and Artificial Intelligence (AI) systems? You will join the AWS Professional Services team to design, implement, and manage AI/ML and GenAI solutions that meet customers’ 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. 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 the team
The AWS Professional Services organization is a global team of experts that helps 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 our global specialty practices. 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 for explaining 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 (data preprocessing, model hosting, feature selection, hyperparameter tuning, distributed & GPU training, deployment, monitoring, 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 and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you need a workplace accommodation during the application and hiring process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner. Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $138,200/year in our lowest geographic market up to $239,000/year in our highest geographic market. Pay is based on factors including market location and job-related knowledge, skills, and experience. This position may include equity, sign-on payments, and other components as part of a total compensation package. For more information, please 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. Job ID: A3041017 Seniority level
Mid-Senior level Employment type
Full-time Job function
Research, Science, and Engineering Industries IT Services and IT Consulting Our goal is to ensure applicants are informed and able to apply. This description contains the essential aspects of the role and responsibilities.
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