Amazon Web Services (AWS)
Delivery Consultant - Machine Learning Engineer, AWS Professional Services, AWS
Amazon Web Services (AWS), Seattle, Washington, us, 98127
Overview
Delivery Consultant - Machine Learning Engineer, AWS Professional Services, AWS Professional Services Join to apply for the Delivery Consultant - Machine Learning Engineer, AWS Professional Services, AWS Professional Services role at Amazon Web Services (AWS). The AWS Professional Services (ProServe) team seeks a skilled ML Engineer to join as a Delivery Consultant. You will work with customers to design, implement, and manage AWS AI/ML and GenAI solutions that meet technical requirements and business objectives. You will lead the implementation process, provide technical guidance, and help customers adopt AI/ML and cloud capabilities. Responsibilities
Implement end-to-end AI/ML and GenAI projects, from understanding business needs to data preparation, model development, deployment, and monitoring. Design and implement machine learning pipelines that are high-performance, reliable, scalable, and secure. Design scalable ML solutions and operations (MLOps) using AWS services and GenAI where applicable. Collaborate with cross-functional teams to prepare, analyze, and operationalize data and AI/ML models. Serve as a trusted advisor to customers on AI/ML, GenAI solutions, and cloud architectures. Share knowledge and best practices within the organization through mentoring, training, publications, and reusable artifacts. Ensure solutions meet industry standards and support 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
Amazon Web Services (AWS) ProServe is a global team helping customers realize business outcomes with the AWS Cloud. We collaborate with customer teams and the AWS Partner Network to execute enterprise cloud initiatives and deliver focused guidance through specialty practices across solutions, technologies, and industries. Basic Qualifications
3+ years of cloud architecture and implementation Bachelor’s degree in Computer Science, Engineering, or related field, or equivalent experience 5+ years in data, software, or ML engineering with strong distributed computing knowledge (data pipelines, training/inference, ML infrastructure) 3+ years developing predictive modeling, NLP, and deep learning; experience building and deploying ML models on cloud (e.g., Amazon SageMaker) 3+ years programming with SQL, Python, and at least one other language (e.g., Java, Scala, JavaScript, TypeScript); proficiency with ML libraries/frameworks (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) Automation and IaC experience (e.g., Terraform, Python; CloudFormation, CDK); containers & CI/CD Knowledge of security and compliance standards (e.g., HIPAA, GDPR) Strong communication skills for technical and non-technical audiences 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 (MLFlow, Kubeflow) and orchestration (Airflow, AWS Step Functions); experience with GenAI technologies (LLMs, Vector Stores, LangChain, Prompt Engineering) Amazon is an equal opportunity employer and does not discriminate on protected statuses. If you need workplace accommodations during the application or hiring process, visit the Amazon accommodations page for more information. Our compensation reflects the cost of labor across US markets. Base pay ranges from $118,200/year to $204,300/year, with variations based on location, knowledge, skills, and experience. This position may include equity or sign-on bonuses as part of a total compensation package. For benefits information, visit the Amazon workplace benefits page. This position will remain posted until filled. Job Details
Company: Amazon Web Services, Inc. Job ID: A2988768
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Delivery Consultant - Machine Learning Engineer, AWS Professional Services, AWS Professional Services Join to apply for the Delivery Consultant - Machine Learning Engineer, AWS Professional Services, AWS Professional Services role at Amazon Web Services (AWS). The AWS Professional Services (ProServe) team seeks a skilled ML Engineer to join as a Delivery Consultant. You will work with customers to design, implement, and manage AWS AI/ML and GenAI solutions that meet technical requirements and business objectives. You will lead the implementation process, provide technical guidance, and help customers adopt AI/ML and cloud capabilities. Responsibilities
Implement end-to-end AI/ML and GenAI projects, from understanding business needs to data preparation, model development, deployment, and monitoring. Design and implement machine learning pipelines that are high-performance, reliable, scalable, and secure. Design scalable ML solutions and operations (MLOps) using AWS services and GenAI where applicable. Collaborate with cross-functional teams to prepare, analyze, and operationalize data and AI/ML models. Serve as a trusted advisor to customers on AI/ML, GenAI solutions, and cloud architectures. Share knowledge and best practices within the organization through mentoring, training, publications, and reusable artifacts. Ensure solutions meet industry standards and support 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
Amazon Web Services (AWS) ProServe is a global team helping customers realize business outcomes with the AWS Cloud. We collaborate with customer teams and the AWS Partner Network to execute enterprise cloud initiatives and deliver focused guidance through specialty practices across solutions, technologies, and industries. Basic Qualifications
3+ years of cloud architecture and implementation Bachelor’s degree in Computer Science, Engineering, or related field, or equivalent experience 5+ years in data, software, or ML engineering with strong distributed computing knowledge (data pipelines, training/inference, ML infrastructure) 3+ years developing predictive modeling, NLP, and deep learning; experience building and deploying ML models on cloud (e.g., Amazon SageMaker) 3+ years programming with SQL, Python, and at least one other language (e.g., Java, Scala, JavaScript, TypeScript); proficiency with ML libraries/frameworks (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) Automation and IaC experience (e.g., Terraform, Python; CloudFormation, CDK); containers & CI/CD Knowledge of security and compliance standards (e.g., HIPAA, GDPR) Strong communication skills for technical and non-technical audiences 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 (MLFlow, Kubeflow) and orchestration (Airflow, AWS Step Functions); experience with GenAI technologies (LLMs, Vector Stores, LangChain, Prompt Engineering) Amazon is an equal opportunity employer and does not discriminate on protected statuses. If you need workplace accommodations during the application or hiring process, visit the Amazon accommodations page for more information. Our compensation reflects the cost of labor across US markets. Base pay ranges from $118,200/year to $204,300/year, with variations based on location, knowledge, skills, and experience. This position may include equity or sign-on bonuses as part of a total compensation package. For benefits information, visit the Amazon workplace benefits page. This position will remain posted until filled. Job Details
Company: Amazon Web Services, Inc. Job ID: A2988768
#J-18808-Ljbffr