Mercari is a Japan-based C2C marketplace company founded in 2013 with the mission to 'Create value in a global marketplace where anyone can buy & sell.' From being the first tech unicorn from Japan before its IPO in 2018 we have come a long way towards becoming a global player and continuously and diligently work towards our transformation journey with a strong focus on our mission.
Since its inception, Mercari Group has worked to grow its services, investing in both our people and technology. Today, Mercari Group is made up of multiple subsidiary businesses including logistics, B2C platform, blockchain, and sports team management.
For our services to be utilized by people worldwide; This endeavor naturally requires the capability of the best talent and minds, and that is exactly the reason for us to launch the India Center of Excellence. With your help, we will continue to take on the world stage and strive to grow into a successful global tech company.
Our organization is also shaped by our four foundations: Sustainability, Diversity & Inclusion, Trust & Openness, and Well-being for Performance. As an AI Engineer in our new AI Taskforce team, you will be at the forefront of designing, developing, and deploying creative AI applications using foundation models (e.g., Large Language Models, Multimodal Models) across Mercari. You will build foundational platforms and services that empower product teams to ship robust, scalable AI-powered features. Build Foundational AI Services: Design, build, and deploy core generative AI applications and services using modern techniques like prompt engineering,



Retrieval-Augmented Generation (RAG), and fine-tuning to solve high-impact problems across the Mercari ecosystem
Drive AI Adoption: Collaborate closely with product, engineering, and infrastructure teams to integrate powerful AI capabilities into the Mercari app, architecting modular and scalable solutions that other teams can build upon
Ensure AI Quality and Safety: Develop and champion robust evaluation pipelines to rigorously measure, monitor, and improve model performance, focusing on accuracy, latency, cost, and responsible AI principles
Lead the Full AI Lifecycle: Own features end-to-end, from problem scoping and prototyping to production deployment, maintenance, and iteration based on quantitative metrics and qualitative user feedback
Stay at the forefront of advancements in AI engineering and share your knowledge to help uplift the technical capabilities of the entire organization
2-6 years of professional software engineering experience, with a demonstrated focus on building and deploying AI/ML-powered systems in production

- Bachelor's or Master's degree in Computer Science, Engineering, or a related field




- Proficiency in Python and hands-on experience building applications with Large Language Models (LLMs) and familiarity with core concepts such as prompt engineering, RAG, and fine-tuning
- Experience building Model Context Protocol(MCP) servers in either Python or Go
- Solid understanding of software engineering fundamentals and the ability to write clean, maintainable, and production-ready code
- Strong problem-solving skills and a data-driven approach to decision-making
- Excellent communication skills to collaborate effectively with both technical and non-technical stakeholders across multiple teams

Experience designing and implementing systematic evaluation strategies for generative AI systems (e.g., AI-as-judge, human-in-the-loop)
Experience with cloud platforms (GCP, AWS, etc.) and containerization technologies (Docker, Kubernetes)
Contributions to open-source projects or publications in top-tier AI/ML conferences
Experience with microservice architecture and development
Employment Status: Full-time
Office: Hybrid workstyle: We believe in high performance and professionalism. We work from the office 2 days/week and work from home 3 days/week
To build a strong & highly-engaged organization in India, we highly encourage everyone to work from our Bangalore office, especially during the initial office setup phase
We will continue to review and update the policy to address future organizational needs
Work Hours: Full flextime (no core time)
Flexible to choose working hours other than team common meetings

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