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Machine Learning Engineer (AI/LLM) - Mercari

Salary not provided

NLPPythonPyTorchTensorFlow
English: Fluent
Mercari

Machine Learning Engineer, AI/LLM

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

Organization & Team Mission

The AI/LLM Team focuses on three core pillars: product, enablement, and research, delivering new AI-driven features and user experiences to maximize product-facing impact. The team works on both independent initiatives and horizontal collaborations with product, engineering, and research teams across the organization.

As a machine learning engineer, you will develop ML architecture and feature engineering solutions impacting multiple business areas, including internal tooling.

Work Responsibilities

  • Develop and Optimize ML Models: Design, build, and optimize machine learning models to solve complex problems, focusing on performance and scalability for large-scale production systems.
  • Feature Engineering: Improve robustness and accuracy of ML models through deep feature engineering, especially in NLP, computer vision, and multimodal learning.
  • Model Deployment and Integration: Integrate ML solutions into existing products and services in collaboration with cross-functional teams.
  • Research and Innovation: Stay updated with the latest research and advancements in AI, machine learning, NLP, and computer vision.
  • Engineering Infrastructure: Design infrastructure to support scalable machine learning systems.
  • Experimentation and Testing: Perform A/B testing and experiments to assess and improve model performance.

Unique Challenges

  • Develop AI-driven solutions with large-scale data, impacting tens of millions of users.
  • Bridge cutting-edge research and practical deployment, translating state-of-the-art AI/LLM into business solutions.
  • Collaborate across teams to build and refine large-scale ML infrastructure.

Qualifications

Required

  • Shared belief in the team's mission and values.
  • Bachelor’s degree in Computer Science, Engineering, or related technical field, or equivalent practical experience.
  • Proficiency in Python and experience with ML frameworks such as PyTorch or TensorFlow.
  • Strong understanding of architectural patterns for large-scale software applications.
  • Experience across the ML lifecycle, from development through to deployment.
  • Strong analytical and problem-solving skills.
  • Excellent written and verbal communication skills.
  • Passion for products and technology.

Preferred

  • Experience deploying AI solutions in large-scale production environments.
  • Master’s or Ph.D. in Computer Science, AI, ML, or related technical field.
  • Background in generative AI, LLM, or NLP.
  • Experience with multilingual/multimodal models and efficient training/inference techniques.
  • Participation in the open-source community and contributions to AI/ML projects.

Language

  • English: Proficient (CEFR - C1)
  • Japanese: Independent (CEFR - B2) (optional)

For details about CEFR, see here.

Recruiting Process Overview

  1. Application screening
  2. Skill assessment: For engineering roles, completion of a skill assessment (HackerRank/GitHub); this may occur during the interview stage.
  3. Interviews: Number may vary by position.
  4. Reference check: Online references are requested near the final interview.
  5. Offer

More information on the recruiting process: Recruitment Selection Process

Equal Opportunity Statement

Hiring is conducted with a commitment to Inclusion & Diversity, eliminating discrimination based on age, gender, sexual orientation, race, religion, disability, or other factors. All candidates aligned with the mission and values are welcomed.

Read the I&D statement.

Please review the Privacy Policy before submitting your application.

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