Employment Type: Full-time
Team: Engineering

本ポジションは日本語JDの用意がありません。

Research Engineer (Applied AI Research) – Mercari

• Employment Status: Full-time
• Work Hours: Full Flextime (no core time)
• Office: Roppongi

For more details, see the Overview of Our Positions section on our Careers site.　　

About Mercari

Circulate all forms of value to unleash the potential in all people

"What can I do to help society thrive with the finite resources we have?" The Mercari marketplace app was born in 2013 out of this thought by our founder Shintaro Yamada as he traveled the world. We believe that by circulating all forms of value, not just physical things and money, we can create opportunities for anyone to realize their dreams and contribute to society and the people around them. Mercari aims to use technology to connect people all over the world and create a world where anyone can unleash their potential. For more information about Mercari Group’s mission, see Mercari’s Culture Doc

Organization/Team Mission

Mercari Engineering Principles  

Mercari Engineering Principles are a shared understanding that serves as the foundation of engineering beliefs and behavior at Mercari. The Engineering Principles are designed to complement the organizational identity (Mercari’s mission, values, and culture) from an engineering viewpoint. 

These principles ultimately help us achieve Mercari’s mission by defining the ideal state we seek to realize in the long term. 

• Passion For The Product
• Grow Together
• Solve Through Mechanisms
• Collaborate Openly

For more details, please see the following link:

• Engineering Culture

Mercari’s Applied AI Research (AAIR) team explores, prototypes, and validates medium‑horizon (6–18 month) applied AI bets that are product‑aligned but execution‑autonomous. We work ahead of the roadmap to de‑risk bold ideas, build working prototypes, and hand off validated directions to product teams. Our team is small by design, operates with high trust and high craft, and communicates impact through functional prototypes and tangible demonstrations with clear paths to product value.

See here for more information about our mission and values.

Work Responsibilities

• Lead end-to-end applied research projects: define experiments, implement prototypes, run evaluations, and hand off reproducible artifacts to product/engineering teams.
• Own at least one deep technical domain (e.g., embedding model design & evaluation, context modeling for agentic systems, on-line or continuous adaptation / fine-tuning pipelines) while contributing across other areas.
• Translate research papers and state-of-the-art approaches into pragmatic, production-aware prototypes and AB-testable experiments.
• Build reliable evaluation pipelines and datasets (offline metrics + human evaluation) and document failures/lessons.
• Mentor and uplevel ML engineering practices across Mercari – techniques, model design, code quality, reproducible experiments, and sound evaluation.
• Collaborate closely with product managers, designers and platform engineers to scope and prioritize research that can move into product, as well as inspire and shape product vision.

Unique Challenges

• Ambiguity > certainty: problems aren’t handed to you; you’ll choose bets, design sensible MVPs, and convince stakeholders with results.
• Small, autonomous team: you’ll set technical direction, engineering standards, and be a multiplier for Mercari’s ML craft.
• Product + science: you must balance SOTA curiosity with constraints of marketplace UX, safety, latency, and data quality.
• Compounding leverage: you’ll create reusable blueprints (data, evaluation, infra) that lift the whole company.

Qualifications

• Required Experience/Skills
• Either one of the following:
• 5+ years building state-of-the-art ML systems in industry
• PhD and 1+ years industry experience
• Strong software engineering skills (Python, PyTorch or TF).
• Demonstrated depth and recent experience in at least one of our core focus areas:
• Semantic Understanding, e.g. multimodal-embeddings, representation learning, or latent variable modelling
• Contextual Intelligence, e.g. graph- or memory-augmented systems, retrieval-augmented generation, or agentic architectures that model user or item context
• Continuous Learning, e.g. preference learning (DPO/variants), reinforcement learning from user feedback (RLHF/RLAIF), or online/continual fine-tuning pipelines
• Strong track record of shipping prototypes or models end-to-end (not just research code).
• Ability to design experiments: dataset creation, metrics, human eval, and interpretable analysis.
• Excellent communication: explain technical tradeoffs to product and engineering audiences.
• Product & UX sense: willingness to frame user problems, success metrics, and UX trade‑offs with PM/Design.
• Comfortable working autonomously in a small, high-focus team that protects flow.

• Preferred Experience/Skills
• Evidence of autonomous research‑to‑product impact (open‑source libraries, internal platforms, or papers with code).
• Previous product or e-commerce experience (valuable but not required).
• Language 
• English: Independent (CEFR - B2) Required
• Japanese: Independent (CEFR - B2) Optional

For details about CEFR, see here. 　

Learn More About Mercari Group

• Careers site: https://careers.mercari.com/en/   
• Mercan: https://mercan.mercari.com/en/  
• Social media: X / Linkedin 

Recruiting at Mercari

At Mercari Group, we value empathizing with and embodying the mission and values ​​of the Group and each company. To promote the creation of an organization that maximizes the total amount of value exhibited by all members, we would like to understand the experience and skills of each candidate as accurately as possible.

Recruiting cycle at Mercari Group

• Application screening
• Skill assessment: For engineering positions, you will be asked to complete a skill assessment on HackerRank or GitHub. For non-engineering positions, you may be asked to complete an assessment depending on the position. (The timing of the assessment may coincide with the interview process.)
• Interview: The number of interviews may vary depending on the position.
• Reference check: We will ask for online references around the timing of the final interview.
• Offer: Offers will be determined carefully in consideration of the final interview and the reference check.

　Learn more about our recruiting process here.

Equal Opportunity Hiring

Here at Mercari, we work to realize a world in which no one’s potential is limited by their background and everyone has the opportunity to freely create value. We also firmly believe that a mindset of Inclusion & Diversity is essential for us to achieve our mission.

This, of course, extends to our hiring practices as well. Mercari is committed to eliminating discrimination based on age, gender, sexual orientation, race, religion, physical disability, and other such factors so that anyone who shares our mission and values can join us, regardless of their background. For more details, please read our I&D statement.

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