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ML Quality Process Lead - Japanese, Customer Engagement Technology - job 1 of 2

Description

The Customer Engagement Technology (CET) organization powers customer service by developing elegant customer and CS Associate (CSA) facing products globally. These products offer effortless self-service and automation solutions to our customers. If customers prefer to interact with a human, we enable CSAs to effectively and elegantly solve customers’ issues using our associate-facing products powered through human-centered design.

We are seeking a ML (Machine Learning) Quality Process Lead, who are fluent in Japanese and English, to join the Omni Machine Learning Data Associate (MLDA) team within CET to help manage quality management processes to analyze, improve annotation, testing, and contact reading accuracy to support new feature and product launches for Customer Service Large Language Models (LLMs).

Key job responsibilities
- Review annotations by paying close attention to details, making necessary adjustments to ensure high-quality data that supports ongoing model improvement.
- Perform root cause analysis using basic data analysis in Excel and SageMaker (annotation tool) on annotations to identify opportunities for improving data accuracy.
- Provide support for ML model training data annotations, assisting annotators in maintaining high-quality work by enforcing best practices.
- Improve Standard Operating Procedures (SOPs) by sharing findings from reviews or deep dives, ensuring a consistent standard of excellence across the team.
- Review LLM testing results provided by testers, paying close attention to details, to ensure their accuracy and identify areas for improvement.
- Carefully monitor the accuracy of multiple annotation projects and proactively communicate any blockers or potential delays in the completion of quality checks.

A day in the life
Amazon offers a full range of benefits that support you and eligible family members, including domestic partners and their children. Benefits can vary by location, the number of regularly scheduled hours you work, length of employment, and job status such as seasonal or temporary employment. The benefits that generally apply to regular, full-time employees include:
1. Medical, Dental, and Vision Coverage
2. Maternity and Parental Leave Options
3. Paid Time Off (PTO)
4. 401(k) Plan

About the team
Omni MLDA ((Machine Learning Data Associate) ) is a team that remotely works to develop and fine-tune generative AI machine learning models and executes testing plans to take the customer service experience to the next level. This is executed by teams of MLDAs working alongside Science and Product/Program Management teams to release localized customer-facing and agent-facing CS solutions, while allowing them to focus on the development of their new products. In addition, teams with existing CS experiences can rely on the Omni MLDA team to keep their solutions up-to-date and push identified technical defects to tech partner teams or defect elimination teams.

Basic Qualifications

- Language fluency in Japanese (Native-level) and English.
- Experience in creating and managing ML annotation processes, testing models, and quality assurance methodologies.
- Analytical and problem-solving skills to identify patterns, inconsistencies, and areas for improvement.
- Ability to thoroughly investigate and identify misalignment between annotations and SOPs, as well as the root causes of inaccuracies.
- Strong ownership and accountability to meet SLAs, and proactive communication regarding blockers, and proposed solutions.
- Ability to collaborate closely with cross-functional teams, understand project/stakeholder requirements, and align annotation efforts and model testing accordingly.

Preferred Qualifications

- Bachelor's Degree
- Experience in annotation
- Familiarity in using Excel
- Experience with project management and stakeholder management

Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, 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 $40,400/year in our lowest geographic market up to $86,500/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. Dependent 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.

Average salary estimate

$63450 / YEARLY (est.)
min
max
$40400K
$86500K

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What You Should Know About ML Quality Process Lead - Japanese, Customer Engagement Technology, Amazon

Are you passionate about machine learning and looking for an exciting opportunity to lead quality processes? Join Amazon as a ML Quality Process Lead in our Customer Engagement Technology (CET) team! In this role, you will utilize your fluency in Japanese and English to ensure the quality of data that fuels our innovative customer service solutions. Your days will be filled with reviewing annotations, performing detailed root cause analysis in Excel and SageMaker, and enhancing our quality assurance methodologies. You'll also collaborate with cross-functional teams, supporting the development of cutting-edge Customer Service Large Language Models (LLMs) and continuously improving our standard operating procedures. At Amazon, we pride ourselves on providing our team members with the tools and environment they need to succeed. With a competitive salary, comprehensive benefits, and a culture that values diversity and innovation, this is the ideal place to advance your career. So if you're ready to make an impact in the world of AI and customer service, we want to hear from you!

Frequently Asked Questions (FAQs) for ML Quality Process Lead - Japanese, Customer Engagement Technology Role at Amazon
What are the key responsibilities of a ML Quality Process Lead at Amazon?

As a ML Quality Process Lead at Amazon, your primary responsibilities include reviewing annotations to ensure high-quality data, conducting root cause analysis for data accuracy, supporting ML model training data annotations, and improving standard operating procedures. You'll also be reviewing LLM testing results and monitoring multiple annotation projects to communicate any potential delays effectively.

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What qualifications are required to become a ML Quality Process Lead at Amazon?

To qualify for the ML Quality Process Lead position at Amazon, candidates must be fluent in Japanese (native level) and English, have experience in managing ML annotation processes, and possess strong analytical skills. A Bachelor's degree is preferred, and familiarity with project management tools and Excel is beneficial.

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How does Amazon support career development for ML Quality Process Leads?

Amazon is dedicated to the career growth of its employees, including ML Quality Process Leads. You will have access to various training resources, mentorship opportunities, and a collaborative environment where you can work with cross-functional teams to develop your skills while bringing innovative solutions to life.

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What tools and technologies do ML Quality Process Leads at Amazon use?

As a ML Quality Process Lead at Amazon, you'll frequently use tools like Excel for data analysis and SageMaker for annotation processes. Familiarity with machine learning concepts and quality assurance methodologies will also be essential for your role.

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What is the work culture like for ML Quality Process Leads at Amazon?

At Amazon, the work culture for ML Quality Process Leads is inclusive and innovative. You will be part of a diverse team where collaboration is encouraged, allowing you to contribute ideas and drive continuous improvements in the customer engagement technology space.

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Common Interview Questions for ML Quality Process Lead - Japanese, Customer Engagement Technology
Can you describe your experience with ML annotation processes?

Be prepared to discuss previous experiences where you've managed ML annotation processes. Highlight specific projects, the tools used, and how you ensured the quality of the annotations. Explain your approach to identifying challenges and solutions in the annotation process.

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How do you conduct root cause analysis to improve data accuracy?

In your response, explain your methodology for root cause analysis. Discuss how you gather data, identify patterns, and leverage tools like Excel or SageMaker to analyze the information. Provide an example of a time when you successfully improved data accuracy through your analysis.

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What are some best practices for maintaining high-quality annotation work?

When answering this question, outline the best practices you've implemented in previous roles to maintain annotation quality. Discuss the importance of training, regular feedback, and adherence to Standard Operating Procedures. Provide examples if possible.

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How do you communicate blockers or potential delays to your team?

Effective communication is vital in collaborative roles. Discuss how you approach sharing blockers with your team, including the timing and method of communication. Highlight the importance of proposing solutions alongside identifying the issue.

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Describe a situation where you had to improve Standard Operating Procedures.

Prepare to discuss any experience you've had in refining SOPs. Explain the process you followed, any challenges you faced, and how your changes positively impacted quality. Use specific examples to illustrate your point.

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How do you ensure accuracy in testing results for ML models?

Explain your approach to reviewing testing results, including the steps you take to validate accuracy. Discuss how you collaborate with testers and what criteria you use to identify areas for improvement in model performance.

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What analytical tools are you most comfortable using for data analysis?

Discuss your experience with specific analytical tools such as Excel, SageMaker, or any other relevant software. Provide examples of how you've used these tools to derive insights from data and improve processes.

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How do you stay updated with the latest trends in machine learning and quality assurance?

Mention the resources you rely on to stay informed, such as industry publications, webinars, online courses, or professional networks. Demonstrating a commitment to ongoing learning is essential in the fast-paced field of machine learning.

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What role does collaboration play in your work as a ML Quality Process Lead?

Emphasize the significance of collaboration in your role. Explain how working alongside cross-functional teams helps to achieve project goals and enhances the quality of your output. Provide a specific example of a successful collaboration.

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Why do you want to work as a ML Quality Process Lead at Amazon?

Articulate your motivation for pursuing this position at Amazon. Discuss the alignment between your skills and passion for machine learning with Amazon's commitment to innovation in customer engagement technology. Highlight any aspects of Amazon’s culture that resonate with you.

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Amazon is guided by four principles: customer obsession rather than competitor focus, passion for invention, commitment to operational excellence, and long-term thinking.

2118 jobs
MATCH
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CULTURE VALUES
Inclusive & Diverse
Rise from Within
Mission Driven
Diversity of Opinions
Work/Life Harmony
Transparent & Candid
Growth & Learning
Fast-Paced
Collaboration over Competition
Take Risks
Friends Outside of Work
Passion for Exploration
Customer-Centric
Reward & Recognition
Feedback Forward
Rapid Growth
BENEFITS & PERKS
Medical Insurance
Paid Time-Off
Maternity Leave
Mental Health Resources
Equity
Paternity Leave
Fully Distributed
Flex-Friendly
Some Meals Provided
Snacks
Social Gatherings
Pet Friendly
Company Retreats
Dental Insurance
Life insurance
Health Savings Account (HSA)
FUNDING
SENIORITY LEVEL REQUIREMENT
INDUSTRY
TEAM SIZE
EMPLOYMENT TYPE
Full-time, on-site
DATE POSTED
March 21, 2025

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