Jobs / Machine Learning Engineer, Search ML- Mercari
Machine Learning Engineer, Search ML- Mercari
Mercari Tokyo | Hybrid
EngineeringMachine Learning Engineer
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Language
EN: Business
JP: None
Salary
Unavailable
See Salary Ranges
Employment Type
Full time
Job Description
- 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.
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
See here for more information about our mission and values.
Responsibilities
- Elevate the Buyer Journey: Drive the optimization of item search and discovery capabilities at Mercari; take end-to-end ownership of core search business logic and user experience design.
- Architect Next-Gen AI Models: Design and deploy state-of-the-art machine learning models and robust training pipelines (incorporating Hybrid Search, Learning-to-Rank, Agentic Shopping, etc.) while continuously enhancing system reproducibility and debuggability.
- Standardize Experimentation Frameworks: Spearhead the development of standardized evaluation and experimentation infrastructure—including offline evaluation frameworks, online A/B testing guardrails, monitoring dashboards, and alerting systems—to accelerate iteration cycles and mitigate regressions.
- Drive Cross-Functional Alignment: Partner seamlessly with infrastructure, product, and adjacent engineering teams to align on scalability, latency, reliability, and cost efficiency, while orchestrating complex, cross-service architectural changes.
Unique Challenges
- High-Velocity C2C Ecosystem: Scale and operate search systems within a highly dynamic, real-time C2C marketplace characterized by rapid inventory turnover (constant new listings, instant sell-outs, frequent price fluctuations) and persistent long-tail/cold-start constraints.
- UGC Semantic Bridging: Bridge the semantic gap between intent-driven user queries and highly fragmented, user-generated content (UGC) that features language-specific variations, slang, mixed scripts, typos, and unstructured brand/model references.
- Cutting-Edge AI Operationalization: Harness and integrate advanced deep learning architectures and Large Language Model (LLM) applications to redefine the modern e-commerce shopping experience.
Qualifications
Required Experience/Skills
- Experience: 5+ years of professional experience in Machine Learning or Search Engineering.
- Search Expertise: Proven track record of optimizing end-to-end search experiences using data-driven methodologies (e.g., hybrid retrieval, learning-to-rank, semantic search, and advanced evaluation metrics).
- Production Engineering: Hands-on experience with production-grade ML/Search serving infrastructure, including one or more of the following: online inference services, feature stores, embedding spaces, evaluation/experimentation tooling, or offline indexing pipelines.
- Research-to-Practice: Demonstrated experience continuously following academic research in your area of expertise (e.g., computer vision, NLP, recommender systems — CVPR, ICCV, ACL, EMNLP, SIGIR, KDD, RecSys, NeurIPS, ICML, etc.) and translating those insights into evaluated, implemented solutions that drove business impact.
- Applied Rigor: Ability to adapt academic techniques to production constraints (latency, scale, cost) and validate impact through methods such as A/B testing.
- Soft Skills: Strong collaborative and communication skills, with a demonstrated ability to align diverse technical teams and cross-functional stakeholders.
Preferred Experience/Skills
- Backend Mastery: 5+ years of software engineering experience focusing on large-scale backend architectures.
- Scale & Performance: Deep technical expertise in large-scale search/recommendation backends, including distributed systems, high-concurrency/low-latency tuning, and complex system debugging.
- Academic Track Record: Publication or peer-review experience at top-tier conferences (e.g., CVPR, ICCV, ECCV, ACL, EMNLP, NAACL, SIGIR, KDD, WWW, RecSys, NeurIPS, ICML, etc.), or a PhD.
- Research Habit: A habit of reading several to ten papers a month to stay current with new methods.
- Technical Leadership: Experience independently driving the technical direction of a team or organization.
- Language
- Japanese: Nice to have (not required)
- English: Business level or above
For details about CEFR, see here.
About The Company
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
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Job Description
- 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.
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
See here for more information about our mission and values.
Responsibilities
- Elevate the Buyer Journey: Drive the optimization of item search and discovery capabilities at Mercari; take end-to-end ownership of core search business logic and user experience design.
- Architect Next-Gen AI Models: Design and deploy state-of-the-art machine learning models and robust training pipelines (incorporating Hybrid Search, Learning-to-Rank, Agentic Shopping, etc.) while continuously enhancing system reproducibility and debuggability.
- Standardize Experimentation Frameworks: Spearhead the development of standardized evaluation and experimentation infrastructure—including offline evaluation frameworks, online A/B testing guardrails, monitoring dashboards, and alerting systems—to accelerate iteration cycles and mitigate regressions.
- Drive Cross-Functional Alignment: Partner seamlessly with infrastructure, product, and adjacent engineering teams to align on scalability, latency, reliability, and cost efficiency, while orchestrating complex, cross-service architectural changes.
Unique Challenges
- High-Velocity C2C Ecosystem: Scale and operate search systems within a highly dynamic, real-time C2C marketplace characterized by rapid inventory turnover (constant new listings, instant sell-outs, frequent price fluctuations) and persistent long-tail/cold-start constraints.
- UGC Semantic Bridging: Bridge the semantic gap between intent-driven user queries and highly fragmented, user-generated content (UGC) that features language-specific variations, slang, mixed scripts, typos, and unstructured brand/model references.
- Cutting-Edge AI Operationalization: Harness and integrate advanced deep learning architectures and Large Language Model (LLM) applications to redefine the modern e-commerce shopping experience.
Required Experience/Skills
- Experience: 5+ years of professional experience in Machine Learning or Search Engineering.
- Search Expertise: Proven track record of optimizing end-to-end search experiences using data-driven methodologies (e.g., hybrid retrieval, learning-to-rank, semantic search, and advanced evaluation metrics).
- Production Engineering: Hands-on experience with production-grade ML/Search serving infrastructure, including one or more of the following: online inference services, feature stores, embedding spaces, evaluation/experimentation tooling, or offline indexing pipelines.
- Research-to-Practice: Demonstrated experience continuously following academic research in your area of expertise (e.g., computer vision, NLP, recommender systems — CVPR, ICCV, ACL, EMNLP, SIGIR, KDD, RecSys, NeurIPS, ICML, etc.) and translating those insights into evaluated, implemented solutions that drove business impact.
- Applied Rigor: Ability to adapt academic techniques to production constraints (latency, scale, cost) and validate impact through methods such as A/B testing.
- Soft Skills: Strong collaborative and communication skills, with a demonstrated ability to align diverse technical teams and cross-functional stakeholders.
Preferred Experience/Skills
- Backend Mastery: 5+ years of software engineering experience focusing on large-scale backend architectures.
- Scale & Performance: Deep technical expertise in large-scale search/recommendation backends, including distributed systems, high-concurrency/low-latency tuning, and complex system debugging.
- Academic Track Record: Publication or peer-review experience at top-tier conferences (e.g., CVPR, ICCV, ECCV, ACL, EMNLP, NAACL, SIGIR, KDD, WWW, RecSys, NeurIPS, ICML, etc.), or a PhD.
- Research Habit: A habit of reading several to ten papers a month to stay current with new methods.
- Technical Leadership: Experience independently driving the technical direction of a team or organization.
- Language
- Japanese: Nice to have (not required)
- English: Business level or above
For details about CEFR, see here.
About The Company
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
Browse Jobs by Role
Design Jobs
Design Design Director Digital Artist Graphic Design
Illustration Motion Graphics Product Design Service Design
UI Design UX Design UX Research UX Writing
Visual Design Video Web Design
Engineering Jobs
Android Engineer iOS Engineer
Front End Developer Back End Developer
Full Stack Developer QA Engineer
Product Jobs
Product Design Product Management
Marketing
Brand Manager Copywriting Marketing Social Media
Operations
Account Executive Project Coordinator Project Manager
Data Jobs
Data Analyst Data Scientist Machine Learning
Other
Gaming Jobs Volunteer Jobs