Machine Learning Engineer, ML Platform

Position Overview

Our organization is rapidly growing as a platform connecting life events, accelerating the transition to an AI-native organization. At the heart of this journey is the machine learning technology that revolutionizes user experience.

The ML Platform Engineer will lead improvements across the ML development environment, from building data pipelines to feature and model serving platforms, and automating tasks using AI. This role supports our ML engineers in focusing on core problem definition and experimentation, enabling easy model application to services with minimal cost and effort.

We prioritize quick experimentation and impactful results on user experience over precise performance metrics. The ML team deeply understands the context of products, users, and business, contemplating how AI/ML can contribute to life.

Key Responsibilities

• Enhance MLOps level and automate the entire modeling workflow, including data processing, training, and deployment.
• Design, develop, and operate components for ML model service applications, such as feature stores, ML models, and recommendation feed serving.
• Provide infrastructure for ML model utilization based on real-time log data.
• Participate in designing and planning AI functions at the user feature level, not just the model level.
• Conduct rapid experiments with stakeholders and integrate them into products.
• Lead experiments and adoption of LLM-based structures like RAG and Agent within products.

Qualifications

• Possess a degree in computer science, machine learning/AI, or equivalent professional knowledge.
• Have over 3 years of practical experience in recommendation/search domains, such as recommendation systems or search algorithms.
• Experience in serving or modeling using Python and major ML frameworks (TensorFlow, PyTorch, etc.).
• Experience in designing and implementing flexible and efficient architectures in constrained environments.
• Experience in developing services based on MSA and deploying operations in a public cloud environment.
• Experience in introducing AI models as actual product features or evaluating their feasibility.

Preferred Qualifications

• Experience in designing and developing backend systems for high-traffic or real-time systems.
• Experience in improving work efficiency through AutoML or ML learning/experiment automation platforms.
• Experience in experimenting with or adopting the latest AI architectures like LLM, vector search, multimodal, etc.
• Experience in effectively explaining, designing, and documenting new models/features to internal teams.
• Experience in collaborating with various stakeholders to define business problems and convert them into ML-based features.
• Interest in our service and user experience, with experience in solving or contemplating real-world problems or improvement ideas.

Application and Process

• Application documents: Resume (required), portfolio, and cover letter (optional) in PDF format recommended.
• Please exclude sensitive personal information such as salary, physical information, family details, and social security numbers.
• Process: Document screening > Coding test > Job interview > Organizational culture interview and reference check > Compensation negotiation > Final acceptance.
• Job interviews may be conducted over 1-2 days depending on the applicant's resume and experience.
• The interview process will include an assessment of AI utilization capabilities.
• Detailed interview processes will be individually guided at the time of the interview.

Additional Information

• This announcement is for rolling recruitment and may close early upon completion of hiring.
• If false information is found in the application documents, employment may be canceled.
• An onboarding program (Move in Program) will be conducted during the 3-month probationary period after joining.
• Veterans and persons with disabilities are given preference according to relevant laws.

Compensation and Benefits

• Generous compensation for talent.
• Stock options granted to all new hires.
• Stock options granted to high contributors.
• Company-wide incentives based on performance.

Work Environment

• Work environment for immersion and growth.
• Flexible working hours (6 AM to 10 PM).
• Free use of vacation without approval.
• Support for breakfast, lunch, and dinner.
• Free support for all menu items at the in-house cafe.
• Support for books, conferences, and education.
• High-end massage chairs in the break room.

Welfare

• Care for long-term collaboration.
• Health checkup support (for self/spouse/parents).
• Group insurance support (for self/spouse/children).
• Refresh leave and long-term service awards.
• Mental care program support.
• Support for experiencing the meaning of our work together.
• Annual support of 1.5 million KRW for decorating your home.
• Upgrade to VIP membership for our service.