Machine Learning Engineer (Deep Learning), Credit ML - Merpay
Minato City, Japan · On-site
Salary not published
Posted 3 weeks ago
From Mercari's careers page
Status: listed on the employer's own careers page when we last checked (daily). Confirm on their site before applying.
About the role
In this position, as a core member responsible for the large-scale deep learning models at the heart of our next-generation credit system, you will play a central role in everything from evaluating model architectures and training strategies to production deployment and…
Machine Learning Engineer (Deep Learning), Credit ML - Merpay
Employment Status: Full-time employee
Work Hours: 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
Merpay Credit Modeling team's mission is to "create a credit business that delivers value to everyone using high-quality data science and machine learning technology." Under this mission, we handle everything from identifying business challenges to model construction, development, and operations.
Currently, the team is working on developing a next-generation credit modeling platform using deep learning. Leveraging diverse data from the Mercari ecosystem, we aim to build versatile foundation models that can be applied to multiple tasks across credit and other domains.
In this position, as a core member responsible for the large-scale deep learning models at the heart of our next-generation credit system, you will play a central role in everything from evaluating model architectures and training strategies to production deployment and continuous improvement.
See here for more information about our mission and values.
Work Responsibilities
Design, development, and improvement of core large-scale deep learning models for next-generation credit modeling:
Model Architecture Design: Designing deep learning model architectures based on the specific challenges and data characteristics of the credit domain.
Training Strategy: Designing training tasks and objective functions; formulating and executing scaling policies considering data, model architecture, and compute budgets.
Training Infrastructure: Designing and implementing GPU-based large-scale and distributed training; optimizing and stabilizing model training processes.
Evaluation Design: Designing evaluations that encompass not only offline metrics, but also key business KPIs, risk metrics, stability, fairness, and explainability critical to credit operations.
Production Deployment & Operations for Large-Scale Deep Learning Models:
Designing training and inference pipelines, optimizing inference efficiency, and integrating models into production systems.
Designing operations for monitoring, retraining, and rollbacks, while building and maintaining robust MLOps practices.
Technical Decision-Making: Determining modeling policies and trade-offs (e.g., model scale/performance vs. cost, inference latency, interpretability, and coexistence with legacy models).
Research & Application: Catching up with the latest research trends in fintech with deep learning and evaluating their application to in-house challenges.
Model operations & Continuous improvements: Operating and continuously improving existing credit models.
Leading consensus-building and collaboration involving stakeholders in product, business, legal, and compliance.
Mentorship & Knowledge Sharing: Providing technical mentorship in deep learning to team members and systematizing knowledge.
Unique Challenges
Build Next-Gen Models from Scratch: Create next-generation deep learning models in the financial domain from the ground up, utilizing the massive and diverse dataset from Mercari—Japan’s largest marketplace app with 24 million MAU.
Pioneer Advanced Deep Learning in Credit: Challenge yourself with cutting-edge initiatives in Japan that apply state-of-the-art deep learning and large-scale training expertise directly to credit scoring and risk evaluation.
High-Stakes Production Implementation: Go beyond R&D to deliver high-stakes, socially responsible production systems, tackling the challenge of creating deep learning models that balance accuracy, stability, explainability, and operational quality.
Social Impact & Financial Inclusion: Embrace "Go Bold" challenges under real-world constraints—such as complex data interpretation, governance, regulations, and risk management—to generate both business value and a broader social impact through financial inclusion.
High Ownership & Career Growth: Join a project in its active development phase, where you will hold significant autonomy in deciding model architectures and training strategies, with opportunities to expand your role into project leadership.
Qualifications
Required Experience/Skills
Someone who can align with the mission and values of the Mercari Group and its companies.
3+ years of experience in deep learning model development using deep learning frameworks such as PyTorch.
1+ year of hands-on experience in pre-training 1B+ parameter Transformer-based models, LLMs, or foundation models from scratch.
Proven experience independently leading model training, experiment design, and result analysis.
1+ year of practical MLOps experience in deploying and operating deep learning models in production environments (or equivalent experience).
Strong communication skills to collaborate smoothly with team members and cross-functional stakeholders.
Preferred Experience/Skills
Experience leading the design of data architectures, model architectures, objective functions, training recipes, and compute budgets for pre-training.
Experience adapting and evaluating pre-trained models for downstream tasks (e.g., fine-tuning, transfer learning).
Experience with training acceleration, optimization, and tuning (e.g., distributed training).
Experience optimizing and accelerating inference (e.g., model compression techniques like knowledge distillation, quantization, pruning, or KV caching).
Experience in tabular data analysis and modeling (deep learning or non-deep learning).
Experience in data analysis and system development in cloud environments such as AWS or Google Cloud.
Experience as a team/project lead, as well as experience mentoring junior engineers.
Experience working in financial institutions or Fintech companies.
Language
Japanese: Proficient (CEFR - C1)
English: Independent (CEFR - B2) Preferred
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 take-home skill assessment. 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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