Machine Learning Engineer (AdTech)

TL;DR

Machine Learning Engineer (AdTech): Developing and optimizing advertising solutions for a high-traffic marketplace with an accent on recommendation systems, matching optimization, and ad classification. Focus on leveraging extensive user behavior and fintech data to drive business impact and improve user experience through advanced ML models.

Location: Hybrid, Minato City, Tokyo, Japan

Company

hirify.global is a leading marketplace app dedicated to circulating all forms of value to help people unleash their potential.

What you will do

• Lead optimization in the Ad-Tech domain to achieve campaign goals and improve advertising effectiveness.
• Develop and maintain ML models for recommendation systems, matching optimization, and ad classification.
• Formulate hypotheses and design evaluation strategies using a data-driven approach to uncover product insights.
• Enhance model performance by leveraging embeddings for images and text.
• Design time-series models to evaluate advertising effectiveness and optimize budget strategies.
• Manage the entire machine learning product lifecycle from planning and proposing to development and deployment.

Requirements

• Proven experience leading optimization in the Ad-Tech domain with a track record of creating significant business impact.
• Proficiency in Python, Go, and SQL.
• Deep understanding of machine learning fundamentals and software engineering, including libraries like scikit-learn and LightGBM.
• Experience designing and executing the full data analysis process from planning to delivery.
• Language: Native Japanese and English B2, OR Native/Fluent English (Japanese as a nice-to-have).
• Location: Must be able to work in a hybrid setup in Tokyo, Japan.

Nice to have

• Experience developing microservices using Kubernetes (k8s).
• Experience building and operating large-scale ETL or ELT pipelines.
• Background in developing recommendation models for advertisements or large-scale search systems.

Culture & Benefits

• Full flextime policy with no core working hours.
• Engineering culture based on passion for the product, open collaboration, and growing together.
• Opportunity to solve challenges for a platform with over 20 million MAUs.
• Inclusive and diverse work environment committed to equal opportunity hiring.

Hiring process

• Application screening followed by a technical skill assessment on HackerRank or GitHub.
• Multiple rounds of interviews to evaluate technical and cultural fit.
• Online reference check prior to the final offer.