Machine Learning Engineer, Deep Learning

Mercari, Inc.

. Design, develop, and improve core large-scale deep learning models for next-generation credit modeling .

Posted 10/23/2026full-timeMinato City • JapanMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and developing large-scale deep learning models, with a strong focus on credit modeling and MLOps practices. Proficient in optimizing training processes and integrating models into production systems while collaborating effectively with cross-functional teams.

Highest-signal resume keywords

Deep Learning Model DevelopmentMLOps ExperiencePyTorch FrameworkJapanese Proficiency (CEFR C1)Transformer-Based Models

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Deep Learning ArchitecturesModel TrainingExperiment DesignObjective Function DesignDistributed TrainingInference OptimizationData AnalysisModel EvaluationScaling PoliciesTraining Pipelines

Soft Skills

Strong Communication SkillsCollaborationMentorship

Tools & Technologies

AWSGoogle CloudGPU-Based TrainingMonitoring ToolsRollback Operations

Industry Keywords

Credit ModelingFintechRisk MetricsBusiness KPIsExplainability

Tech Stack

Tools & technologies

AWSCloudPyTorch

About the role

Key responsibilities & impact

Design, develop, and improve core large-scale deep learning models for next-generation credit modeling
Design deep learning architectures based on credit-domain challenges and data characteristics
Design training tasks and objective functions, and formulate and execute scaling policies based on data, model architecture, and compute budgets
Design and implement GPU-based large-scale and distributed training, optimizing and stabilizing training processes
Design evaluations covering offline metrics, business KPIs, risk metrics, stability, fairness, and explainability
Design training and inference pipelines, optimize inference efficiency, and integrate models into production systems
Design monitoring, retraining, and rollback operations and build robust MLOps practices
Make technical modeling decisions involving scale versus performance and cost, inference latency, interpretability, and legacy-model coexistence
Track latest deep learning research and evaluate applications to in-house challenges
Operate and continuously improve existing credit models
Build consensus and collaborate with product, business, legal, and compliance stakeholders
Provide technical deep learning mentorship and systematize team knowledge

Requirements

What you’ll need

Alignment with Mercari Group and company missions and values
3+ years of experience developing deep learning models using frameworks such as PyTorch
1+ year of hands-on experience pre-training 1B+ parameter Transformer-based models, LLMs, or foundation models from scratch
Experience independently leading model training, experiment design, and result analysis
1+ year of practical MLOps experience deploying and operating deep learning models in production, or equivalent experience
Strong communication skills for collaboration with team members and cross-functional stakeholders
Japanese proficiency at CEFR C1
English proficiency at CEFR B2 is preferred
Preferred: experience leading pre-training data/model architecture, objective function, training recipe, and compute budget design
Preferred: experience applying and evaluating pre-trained models for downstream tasks, including fine-tuning and transfer learning
Preferred: distributed training acceleration, optimization, and tuning experience
Preferred: inference acceleration and optimization, including knowledge distillation, quantization, pruning, and KV caching
Preferred: tabular data analysis and modeling experience
Preferred: data analysis and system development in AWS, Google Cloud, or similar cloud environments
Preferred: team or project leadership and junior engineer mentoring experience
Preferred: experience working in financial institutions or Fintech companies

Benefits

Comp & perks

Flextime with no core time
Full-time employee status
Opportunities for career growth into project leadership
Significant autonomy in model architecture and training strategy decisions