Senior Delivery Consultant - Senior Machine Learning Engineer, AWS Professional Services, AWS P
Listed on 2025-12-01
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IT/Tech
AI Engineer, Machine Learning/ ML Engineer, Cloud Computing, Data Engineer
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, AWS Professional Services role at Amazon Web Services (AWS).
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 Amazon Web Services Professional Services (Pro Serve) team is seeking a skilled ML Engineer to join our team as a Delivery Consultant at Amazon Web Services (AWS). In this role, you'll 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, act as a technical leader, and perform hands‑on development of ML solutions with exceptional quality.
Possessing a deep understanding of AWS products and services, you will be proficient in architecting complex, scalable, and secure AI/ML and GenAI solutions tailored to each customer. You’ll work closely with stakeholders to gather requirements, assess current infrastructure, and propose effective migration strategies to AWS. As a trusted advisor, you will guide customers on industry trends, emerging technologies, and innovative solutions, while leading implementation, ensuring best‑practice adherence, optimizing performance, and managing risk throughout the project lifecycle.
Key Job Responsibilities- Lead project teams and 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 MLOps solutions using AWS services and leverage GenAI solutions when applicable.
- Collaborate with cross‑functional teams (Applied Science, Dev Ops, Data Engineering, Cloud Infrastructure, Applications) 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.
- 5+ years of cloud architecture and implementation experience.
- Bachelor’s degree in Computer Science, Engineering, or related field (or equivalent experience).
- 8+ years leading technical teams and hands‑on experience in data, software, or ML engineering, with strong distributed‑computing knowledge (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 Sage Maker).
- 5+ years developing with SQL, Python, and at least one additional programming language (Java, Scala, JavaScript, Type Script). Proficient with leading ML libraries and frameworks (Tensor Flow, PyTorch).
- AWS experience and proficiency in AWS services such as Sage Maker, Bedrock, EC2, ECS, EKS, Open Search, Step Functions, VPC, Cloud Formation.
- AWS Professional certifications (Solutions Architect Professional, Dev Ops Engineer Professional, etc.).
- Experience with automation (Terraform, Python), Infrastructure as Code (Cloud Formation, CDK), Containers, and CI/CD pipelines.
- Knowledge of common security and compliance standards (HIPAA, GDPR).
- Strong communication skills and ability to explain complex concepts to technical and…
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