Staff Machine Learning Engineer (AI)

TL;DR

Staff Machine Learning Engineer (AI): Designing and building state-of-the-art machine learning systems and scalable model servers for a programmatic advertising engine with an accent on deep neural network models and large-scale data pipelines. Focus on developing high-QPS, low-latency prediction systems and defining future product roadmaps.

Location: Onsite in Seoul, South Korea

Company

hirify.global is a product company that builds powerful AI advertising solutions to democratize access to advanced AI for businesses globally.

What you will do

• Design state-of-the-art machine learning models using Tensorflow for real-world, large-scale problems.
• Construct and maintain data pipelines for model training and serving using Google cloud products.
• Develop highly scalable model servers on cloud platforms.
• Work with product, account, and infrastructure engineering teams to define future product roadmaps.

Requirements

• MS or Ph.D. degree in Computer Science or a related technical field.
• 7+ years of software development experience in Machine Learning, Deep Learning related areas.
• Fluent with one or more programming languages including Python, Java, and Golang.
• Knowledgeable with production-level machine learning applications including Natural Language Processing, computer vision, recommendation systems, and ranking systems.
• Experience in building a highly scalable model or online service system.
• Fluent in speaking and writing English.

Nice to have

• Relevant experience in AdTech.

Culture & Benefits

• Focus on inclusion, authenticity, and belonging, where everyone's voice is respected and valued.
• Promotes an uncapped growth mindset, encouraging curiosity, diverse perspectives, and experimentation.
• Committed to creating real value and helping customers succeed through rigor, integrity, and disciplined trade-offs.
• Fosters a collaborative and equitable workplace where teams go further together.
• Offers innovative benefits that empower employees to care for themselves and their families.