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Sr. NLP Engineer - Japanese シニア自然言語処理エンジニア, Alexa Japan

Amazon

Sr. NLP Engineer - Japanese シニア自然言語処理エンジニア, Alexa Japan

Amazon

Tokyo, 13, JPN

·

On-site

·

Full-time

·

3w ago

必須スキル

Python

Amazon is seeking a senior natural language processing engineer to own the Japanese language experience for Alexa. This hybrid product and language technology role combines product strategy ownership with hands-on language engineering expertise to build and localize GenAI technology for the Japan market. As the single-threaded owner of the Japanese language capability bar, you will define the vision, roadmap, and success metrics while providing direct technical and linguistic support to global teams across ASR, TTS, NLU, and conversational AI. This high-visibility role impacts millions of Japanese customers and establishes Amazon's AI voice leadership in Japan.

You will shape the future of Japanese AI voice technology at the intersection of product strategy and cutting-edge language technology. The ideal candidate is equally comfortable writing a product vision narrative for senior leadership as designing test sets to measure Japanese pitch accent accuracy, diagnosing error patterns, or automating evaluation pipelines. You can conduct deep dive analysis on language performance and bring compelling data to motivate change. You will work across Applied Science, Engineering, QA, UX, and business stakeholders in a fast-paced, ambiguous environment, structuring problems into actionable frameworks that drive measurable outcomes.

Key job responsibilities

  • Product Strategy & Ownership

  • Define and own the product vision, strategy, roadmap, and success metrics for Japanese language capabilities in Alexa, including competitive benchmarking

  • Drive product discussions and executive communication in both Japanese and English; bridge Japanese market needs and global technical capabilities, ensuring cultural and linguistic complexities are addressed in product development

  • Influence cross-functional roadmaps and engineering priorities through data-driven contributions; make smart trade-offs across initiatives, balancing short-term delivery against long-term strategic goals

  • Own end-to-end launch execution and post-launch quality monitoring, defining showstoppers and ensuring issues are triaged and resolved in priority order

  • Language Technology & Data Expertise

  • Design evaluation test sets, define quality metrics, and establish regression testing and benchmarking methodologies for Japanese language performance across key user journeys, in partnership with QA and science teams

  • Produce, process, and analyze language data to diagnose quality issues and inform product and modeling decisions; automate evaluation and data workflows using Python and/or internal NLP tooling

  • Partner with Applied Scientists on training data requirements and the customer impact of architectural and data decisions for Japanese; provide Japanese language engineering support to global teams including data collection design, annotation guideline authoring, quality auditing, and model evaluation

  • Identify and proactively communicate pitfalls unique to Japanese language and speech technology (e.g., homograph and homophone disambiguation, pitch accent assignment, argument and topic omission, appropriate keigo use in response generation) and develop mitigation strategies

A day in the life
Your morning kicks off designing an evaluation taxonomy for Japanese entertainment use cases with Applied Scientists. You map real utterance patterns against failure modes the model struggles with and ensure statistical coverage that catches real problems, not just easy ones. Next, you dig into a model benchmarking exercise with the QA team, comparing candidate models across performance metrics including Japanese-specific signals like pitch accent. By late afternoon, you're writing a technical explainer for a US engineering team, walking them through how Japanese orthographic complexity and compounding homophone ambiguity create failure modes they'll never see in English.

Basic Qualifications

  • 5+ years of experience in product management for language or speech technology products, or in language engineering with demonstrated product ownership, in AI/ML, voice technology, or NLP
  • Native Japanese speaker with deep understanding of linguistic nuances, honorific systems, and cultural context; professional-level English proficiency
  • Strong understanding of LLMs, speech technologies (e.g. ASR, TTS, NLU), and their key performance drivers
  • Demonstrated ability to work with language data: design evaluation sets, analyze error patterns, and automate data workflows using Python or equivalent scripting language
  • Proven experience working with science and engineering teams on complex technical products, with strong written and verbal communication skills for executive audiences

Preferred Qualifications

  • Advanced degree (Master's or PhD) in Computational Linguistics, NLP, Language Technology, Linguistics, or Computer Science
  • Hands-on experience with speech technology evaluation or building language artifacts (e.g. pronunciation lexicons, text normalization rules, evaluation scripts)
  • Experience with Japanese language technology specifically, including Japanese phonology, orthographic complexity, and sociolinguistic variation
  • Experience with synthetic/model-based data generation, LLM-as-a-judge evaluation, or human-in-the-loop annotation workflows

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.

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Amazonについて

Amazon

Amazon

Public

Amazon.com, Inc. is an American multinational technology company engaged in e-commerce, cloud computing, online advertising, digital streaming, and artificial intelligence.

10,001+

従業員数

Seattle

本社所在地

$1.5T

企業価値

レビュー

2.9

10件のレビュー

ワークライフバランス

2.8

報酬

3.7

企業文化

2.5

キャリア

2.3

経営陣

2.1

35%

友人に勧める

良い点

Good pay and compensation

Strong benefits package

Flexible scheduling options

改善点

Poor management and leadership

Limited growth and promotion opportunities

High stress and demanding work environment

給与レンジ

4件のデータ

L2

L3

L4

L5

L6

L2 · Data Analyst L2

0件のレポート

$108,330

年収総額

基本給

$43,332

ストック

$54,165

ボーナス

$10,833

$75,831

$140,829

面接体験

10件の面接

難易度

3.7

/ 5

期間

21-35週間

内定率

20%

体験

ポジティブ 10%

普通 10%

ネガティブ 80%

面接プロセス

1

Application Review

2

Recruiter Screen

3

Online Assessment

4

Technical Phone Screen

5

Onsite/Virtual Loop

6

Team Matching

7

Offer

よくある質問

Coding/Algorithm

System Design

Behavioral/STAR

Leadership Principles

Technical Knowledge