Delivery Consultant - Machine Learning Engineer, AWS Professional Services, AWS Professional Se[...]

Overview

Delivery Consultant - Machine Learning Engineer, AWS Professional Services

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)? Eager to learn to apply AI/ML to a diverse array of enterprise use cases? This role involves designing, implementing, and managing AWS AI/ML and GenAI solutions that meet technical requirements and business objectives, and driving customer success throughout the ML project lifecycle.

Responsibilities

1. Implement end-to-end AI/ML and GenAI projects, from understanding business needs to data preparation, model development, deployment and monitoring.
2. Design and implement machine learning pipelines that support high-performance, reliable, scalable, and secure ML workloads.
3. Design scalable ML solutions and operations (MLOps) using AWS services and leverage GenAI solutions when applicable.
4. Collaborate with cross-functional teams (Applied Science, DevOps, Data Engineering, Cloud Infrastructure, Applications) to prepare, analyze, and operationalize data and AI/ML models.
5. Serve as a trusted advisor to customers on AI/ML and GenAI solutions and cloud architectures.
6. Share knowledge and best practices within the organization through mentoring, training, publication, and creating reusable artifacts.
7. 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.

Qualifications

• Basic qualifications: AWS experience preferred, with proficiency in a range of AWS services (e.g., SageMaker, Bedrock, EC2, ECS, EKS, OpenSearch, Step Functions, VPC, CloudFormation).
• Preferred qualifications: 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 with ability to explain complex concepts to technical and non-technical audiences.
• 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 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).

About AWS and Inclusion

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 have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding 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 in our lowest geographic market up to $204,300/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Depending on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. 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.

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Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.