Applied Science Manager, Artificial General Intelligence , Quality Automation

Amazon; Bellevue (WA); On-site; USD 184,000 - 249,000; Full time

Benefits offered by this job

Health insurance

RSUs

Paid time off

Parental leave

Job summary

Amazon seeks an Applied Science Manager for the AGI team to lead a group of scientists and engineers focused on data quality, auditing, and automated evaluation of LLMs and multimodal systems. You will design quality frameworks, recruit and coach staff, and partner with senior leadership to shape product strategy.

The role combines people leadership with hands-on ML work, including building auditing rubrics, judge architectures, and data-collection workflows, to deliver high-quality training

Qualifications

• 3+ years of scientists or machine learning engineers management experience.
• Knowledge of ML, NLP, Information Retrieval and Analytics.

Responsibilities

• Lead and mentor a team of Applied Scientists to develop quality strategies and auditing frameworks.
• Design auditing strategies with SOPs, quality metrics, and sampling methodologies.
• Oversee expert-level manual audits, meta-audits, and coaching to uplift quality.
• Manage development of LLM-as-a-Judge systems and evaluation models.
• Recruit, hire, and develop team members; communicate with senior leadership.

Skills

ML leadership

Quality assurance leadership

Job description

Applied Science Manager, Artificial General Intelligence , Quality Automation

Job ID: 10486373 | Amazon.com Services LLC

The Artificial General Intelligence (AGI) team is seeking a dedicated, skilled, and innovative Applied Science Manager with a robust background in machine learning, statistics, quality assurance, auditing methodologies, and automated evaluation systems to lead a team ensuring the highest standards of data quality, to build industry-leading technology with Large Language Models (LLMs) and multimodal systems.

Key job responsibilities

As part of the AGI team, an Applied Science Manager will lead and mentor a team of Applied Scientists who develop comprehensive quality strategies and auditing frameworks that safeguard the integrity of data collection workflows. The manager will guide the team in designing auditing strategies with detailed SOPs, quality metrics, and sampling methodologies that align with core scientist team developing Amazon Nova models. The Applied Science Manager will oversee expert-level manual audits, meta-audits to evaluate auditor performance, and provide coaching to uplift overall quality capabilities across the team. A critical aspect of this role involves managing the development and maintenance of LLM-as-a-Judge systems, including designing judge architectures, creating evaluation rubrics, and building machine learning models for automated quality assessment. The Applied Science Manager will also oversee the configuration of data collection workflows and ensure effective communication of quality feedback to stakeholders. The manager will have a direct impact on enhancing customer experiences through high-quality training and evaluation data that powers state-of-the-art LLM products and services.

The Applied Science Manager will be responsible for recruiting, hiring, and developing team members, conducting performance reviews, setting clear expectations and growth plans, and fostering a culture of scientific excellence and innovation. The manager will communicate with senior leadership, cross-functional technical teams, and customers to collect requirements, describe product features and technical designs, and articulate product strategy.

A day in the life

An Applied Science Manager with the AGI team will lead quality solution design, guide root cause analysis on data quality issues, drive research into new auditing methodologies, and find innovative ways of optimizing data quality while setting examples for the team on quality assurance best practices and standards. The manager will work closely with talented engineers, domain experts, and vendor teams to put quality strategies and automated judging systems into practice. The manager will also conduct regular 1:1s with team members, provide mentorship and coaching, and ensure the team delivers high-impact results aligned with organizational goals.

Basic Qualifications

• 3+ years of scientists or machine learning engineers management experience
• Knowledge of ML, NLP, Information Retrieval and Analytics

Preferred Qualifications

• Experience building machine learning models or developing algorithms for business application
• Experience building complex software systems, especially involving deep learning, machine learning and computer vision, that have been successfully delivered to customers

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.

The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits.

USA, WA, BELLEVUE - 183,800.00 - 248,700.00 USD annually

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