AmazonPosted 1w ago

Professional Services II - AMZ27134.3

Professional Services II - AMZ27134.3 at Amazon scores 90 out of 100 on AI centrality, which makes it AI Level 4 of 4 (Builds AI) on this board. The level measures how much of the work is AI, not seniority.

US, NY, New Yorkmidfull-time$145k-$195k

AI in this role

Professional services engineer implementing end-to-end AI/ML and generative AI projects, pipelines, and MLOps practices on AWS.

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ragfine-tuningml-opsmachine-learningmlopsgenerative-aicloud-architecture

Employer: Amazon Web Services, Inc.
Position: Professional Services II - AMZ27134.3
Location: New York, NY

Multiple Positions Available:

Implement end-to-end AI/ML and GenAI projects, including scoping business problems, preparing and cleaning data, developing models, and deploying them into production with monitoring and retraining processes. Build and manage machine learning pipelines using AWS services(e.g., SageMaker, Step Functions, Lambda, CloudWatch) to ensure scalable, reliable, and secure ML workloads. Apply MLops practices(CI/CD for ML models, automated testing, containerization with Docker/ECR, and model registry/versioning) to streamline deployment and governance of AI/ML solutions. Leverage GenAI models and frameworks(e.g., Llama, Hugging Face Transformers, Lang Chain) to design retrieval-augmented generation (RAG) applications, text-to-SQL solutions, and domain-specific fine-tuning. Collaborate daily with cross-functional teams—including Applied Scientists, Data Engineers, DevOps, and Cloud Infrastructure engineers—to prepare datasets, optimize model performance, and integrate solutions into enterprise systems. Assist customers, review their use cases, recommending AI/ML architectures, and guiding adoption of cloud-native and GenAI best practices. Share knowledge across the organization by conducting internal training sessions, publishing technical artifacts, and mentoring junior engineers, contributing to a growing repository of reusable AI/ML assets.

10% of work time may be spent in domestic travel to perform the job duties.

(40 hours / week, 8:00am-5:00pm, Salary Range $144500 - $195400)

Amazon.com is an Equal Opportunity – Affirmative Action Employer – Minority / Female / Disability / Veteran / Gender Identity / Sexual Orientation

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Basic qualifications

Must have at least a Master’s degree or foreign equivalent in Computer Science, Engineering (any field), Applied Analytics, or related field and 1 year of experience in job offered or related occupation.
Experience must include at least 1 year in each of the following:
1) Data analysis and processing using Python and SQL
2) Machine Learning and Statistical Modeling
3)Software Engineering practices including version control, testing, and CI/CD
4) Generative AI system design

The base pay range for this position in New York City is USD $144500 - $195400 (yr). Pay is based on market location and may vary depending on job-related knowledge, skills, and experience. A sign-on payment and restricted stock units may be provided as part of the compensation package, in addition to a full range of medical, financial, or other benefits, dependent on the position offered. Applicants should apply via Amazon's internal or external careers site.

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Preferred qualifications

All applicants must meet all the above listed requirements.

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.

Prepare for this job

A free preview built only from this posting: what it asks for, what you could be asked in an interview, and how to adjust your resume.

Skills and AI tools this role asks for

RagFine TuningMl OpsMachine LearningMlopsGenerative AICloud ArchitectureLlama

Questions you could be asked

How would you design a retrieval step so the model answers from real data instead of guessing?
Walk me through fine-tuning a model: what data did you use, and how did you check the result?
How do you monitor a model once it's live, and how do you know it needs retraining?
Tell me about a project where machine learning was part of your work. What did you do?
Tell me about a project where mlops was part of your work. What did you do?

Adapt your resume

List these exact terms on your resume: Rag, Fine Tuning, Ml Ops, Machine Learning, and Mlops. An applicant tracking system matches the wording, not the idea.
Attach one line of real, concrete experience to at least one of them — a tool named with nothing behind it rarely survives a human read.
Lead with what you built, trained or shipped — this role is judged on the AI system itself, not the tools around it.

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