Machine Learning Engineer (Recommendation)

TL;DR

Machine Learning Engineer (Recommendation): Building and optimizing machine learning systems for personalized news experiences with an accent on ranking strategies, user engagement, and monetization. Focus on designing ranking models, conducting large-scale A/B testing, and refining the recommendation pipeline for high-scale user data.

Location: Hybrid in Tokyo, Japan. Visa sponsorship and overseas relocation support available for eligible candidates.

Company

hirify.global is a leading global information and news discovery company dedicated to delivering quality information to millions of users via unique ML technology.

What you will do

• Translate business objectives and product requirements into scalable ranking strategies and machine learning solutions.
• Design, develop, and iterate on ranking models and features for 'For You', Push Notifications, Search, and Ads.
• Lead end-to-end experimentation, including hypothesis formation, offline evaluation, and A/B testing.
• Analyze large-scale user behavior data to identify opportunities and diagnose performance gaps.
• Collaborate with Product, Business, and Engineering teams to define success metrics and prioritize initiatives.
• Refine the recommendation pipeline by improving modeling approaches and feature effectiveness.

Requirements

• Business-level proficiency in Japanese for collaboration with local stakeholders.
• Bachelor's or Master's degree in Computer Science, Engineering, Statistics, Mathematics, or a related quantitative field.
• Strong foundation in ML fundamentals (supervised learning, model evaluation, feature engineering).
• Proficiency in Python and experience with ML frameworks such as PyTorch or TensorFlow.
• Experience with data processing tools (SQL, Pandas, Spark) and handling large-scale datasets.
• Understanding of A/B testing and basic statistical analysis.

Nice to have

• Experience in recommendation systems, ranking, search, ads, or personalization domains.
• Hands-on experience with distributed training environments or Spark.
• Familiarity with deep learning models (embeddings, sequence models, multi-task learning).
• Exposure to production ML workflows, model deployment, and monitoring.
• Contributions to open-source projects, research publications, or Kaggle competitions.

Culture & Benefits

• Full healthcare and social insurance as required by Japanese labor law.
• Annual health checks provided.
• Visa sponsorship and overseas relocation support.
• Global startup environment with offices in Tokyo, Osaka, Palo Alto, New York, and Singapore.