Level

AmazonPosted 3d ago

L3

Manager I, ML Data Operations, AGI Data Services - Operations

Manager I, ML Data Operations, AGI Data Services - Operations at Amazon scores 65 out of 100 on AI centrality, which makes it a Level 3 role on this board.

CR, H, Herediamidfull-time

AI in this role

Lead a team of ML data associates delivering labeled training data for Amazon's speech and language AI models.

ai-data-labelingteam-managementdata-operationsmachine-learning-dataprocess-improvementkaizensix-sigma
We are looking for a Team Manager with experience driving process improvements and operational excellence to lead operations in our San José site.

Lead a team of 20+ Machine Learning Data Associates responsible for delivering high-quality labeled data that trains Amazon's AI models. Our team provides the foundational training data that powers Amazon's generative AI products across Speech and Language Solutions (SLS).

Key job responsibilities
Lead and develop a team of approximately 20+ ML Data Associates, including scheduling, attendance tracking, and leave approvals.

Deliver on known Service Level Agreements and task completion targets (within provided capacity) for specific customers, workflows, and delivery priorities.

Ensure ML data workflows are quality compliant. Analyze ML data, tickets, productivity, and efficiency metrics.

Identify risks and ensure escalations reach the right people. Adhere to confidentiality and compliance requirements.

Liaise with Program Management and other global operations team leads to manage risks and propose mitigation strategies.

Provide structured feedback and development guidance to direct reports through regular 1:1s and performance conversations.

Identify and help implement process-related improvements using methodologies such as Kaizen, Six Sigma, or Lean.

Present data in business meetings/reviews.

Manage performance through Amazon's structured processes, including performance improvement plans and hiring recommendations in partnership with HR.

Deliver clear written and verbal communication in English and Spanish to support team alignment, stakeholder updates, and documentation requirements.

A day in the life
Your day starts with a review of overnight metrics — quality scores, throughput, attendance, and SLA status. You will address any immediate escalations (associate questions, tool issues, or capacity gaps) and align with site leadership during the daily check-in.

Expect to spend approximately 30–40% of your time in meetings: daily standups with your team, weekly syncs with partner teams, business
reviews, and cross-functional planning sessions. Another 30% goes to people leadership: 1:1s with your 20+ direct reports on a rotating schedule, performance conversations, coaching sessions, leave approvals, and attendance tracking.

The remaining time is split between reporting (analyzing metrics, preparing status updates, analyzing trends) and operational problem-solving (shift coverage, backfill requests, process escalations). During peak periods or attrition spikes, you

About the team
Knowledge Fulfillment Engine – Frontier AI Data Services provides high-quality labeled data at speed for machine learning technologies that power Amazon's AI products. Your labeled data feeds directly into AI model training, though you may not always see the final product your work enables, the labeled data your team provides is the engine that drives AI Model development growth for Amazon and our customers.

Basic qualifications

- Bachelor's degree in a relevant field (e.g., Business Administration, Liberal Arts, Sciences, Computer Science, Engineering, Social Sciences, Education, Communication, Visual and Performing Arts, Translation and Interpretation).
- 12+ months of people leadership experience leading teams of 20+ direct reports.
- Advanced proficiency in English and Spanish across verbal, written, reading, and comprehension skills
- Experience in understanding performance metrics and developing them to measure progress against KPIs.
- Experience managing process and operational escalations.
- Microsoft Office proficiency and ability to pull data from numerous databases
- Demonstrated ability to manage competing priorities and adjust to evolving business needs.
- Analytical, problem-solving, and logical reasoning skills. Ability to collaborate effectively with team members and stakeholders.

Preferred qualifications

- Advanced proficiency in English language (CEFR C1+)
- 12+ months of hands-on experience in FAI operations, including familiarity with AI data annotation workflows, quality assurance processes, and production metrics
- Experience with process improvement/quality control tools and methods
- Demonstrated ability to lead diverse talent within a team, work cross-functionally
- Experience providing structured feedback and development guidance through regular 1:1s and performance conversations.
- Experience with aspects of speech and language technology
- Master's Degree in a relevant field
- Working Knowledge of Machine Learning and Large Language Models
- Organizational skills with exceptional follow-through and attention to detail

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

AI Data LabelingTeam ManagementData OperationsMachine Learning DataProcess ImprovementKaizenSix Sigma

Questions you could be asked

  1. How do you keep labeling instructions consistent across a large annotation team?
  2. Tell me about a project where team management was part of your work. What did you do?
  3. Tell me about a project where data operations was part of your work. What did you do?
  4. Tell me about a project where machine learning data was part of your work. What did you do?
  5. Tell me about a project where process improvement was part of your work. What did you do?

Adapt your resume

  • List these exact terms on your resume: AI Data Labeling, Team Management, Data Operations, Machine Learning Data, and Process Improvement. 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.
  • Show where AI is part of your daily process, not a one-off project — this role expects it to be a running habit.

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