Amazon Web Services (AWS)
Delivery Consultant - Machine Learning Engineer, AWS Professional Services
Amazon Web Services (AWS), New York, New York, us, 10261
Overview
Delivery Consultant - Machine Learning Engineer, 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 design, implement, and manage AWS AI/ML and GenAI solutions for customers, driving success through the ML project lifecycle and providing technical expertise and best practices. 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 support high-performance, reliable, scalable, and secure ML workloads. 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, and creating 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. Basic Qualifications
3+ years cloud architecture and implementation Bachelor's degree in Computer Science, Engineering, related field, or equivalent experience 5+ years data, software, or ML engineering, with strong understanding of distributed computing (data pipelines, training and inference, ML infrastructure design) 3+ 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) 3+ 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 a range of 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 (Terraform, Python), Infrastructure as Code (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 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) Company
- Amazon Web Services, Inc. Job ID : A2983399 Other Details
Location: New York, United States. The position is full-time. Employment types include Full-time. Seniority level not applicable. Industry: IT Services and IT Consulting. This position will remain posted until filled. 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 during the application or 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 $118,200/year to $204,300/year, depending on location and experience. Amazon is a total compensation company. Depending on the position, equity, sign-on payments, and other benefits may be provided. For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits.
#J-18808-Ljbffr
Delivery Consultant - Machine Learning Engineer, 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 design, implement, and manage AWS AI/ML and GenAI solutions for customers, driving success through the ML project lifecycle and providing technical expertise and best practices. 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 support high-performance, reliable, scalable, and secure ML workloads. 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, and creating 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. Basic Qualifications
3+ years cloud architecture and implementation Bachelor's degree in Computer Science, Engineering, related field, or equivalent experience 5+ years data, software, or ML engineering, with strong understanding of distributed computing (data pipelines, training and inference, ML infrastructure design) 3+ 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) 3+ 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 a range of 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 (Terraform, Python), Infrastructure as Code (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 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) Company
- Amazon Web Services, Inc. Job ID : A2983399 Other Details
Location: New York, United States. The position is full-time. Employment types include Full-time. Seniority level not applicable. Industry: IT Services and IT Consulting. This position will remain posted until filled. 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 during the application or 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 $118,200/year to $204,300/year, depending on location and experience. Amazon is a total compensation company. Depending on the position, equity, sign-on payments, and other benefits may be provided. For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits.
#J-18808-Ljbffr