ML Software Engineering Team Leader (HYPERCONNECT AI)

[AI Lab]

Hyperconnect AI Lab innovates user experience by finding and solving problems that are difficult to approach with existing technologies but can be solved through machine learning technology in services that connect people. To this end, we develop numerous models in various domains including video/audio/natural language/recommendation, and aim to contribute to the growth of actual services by solving problems encountered while stably providing them through mobile and cloud servers. Under this goal, Hyperconnect AI Lab has been developing machine learning technologies that contribute to Hyperconnect's products, including Azar, for several years.

[ML Software Engineering Team]

Hyperconnect MLSE Teams apply machine learning technology to services through software engineering in services that connect people, innovating user experience.

We apply numerous models in various domains, including video/audio/text/recommendation, created by the in-house AI organization, to production, solve engineering problems encountered while stably providing them through mobile and cloud servers, and aim for the technology we create to contribute to the growth of actual services.

To achieve this goal, we (1) develop scalable backend servers based on ML models, (2) develop/operate real-time data pipelines for ML model inference, and (3) perform platformization of ML components that can be commonly managed in collaboration with other teams. In the process, we work closely with other roles and participate in all necessary processes (problem definition, hypothesis setting, experiment design, analysis, and feedback) to achieve KPI goals, leading our work proactively.

• [[How AI Lab Works] ML Application Team](https://career.hyperconnect.com/post/658d53c249d33b00016865c0)
• [[How AI Lab works] AIP Dev Team](https://career.hyperconnect.com/post/65e04af8f6ab450001c2543e)
• [[How AI Lab Works] Head of AI](https://career.hyperconnect.com/post/64d1ffea7b0f3d00016fc4e7)

[Job Responsibilities]

The ML Software Engineering Team Leader at Hyperconnect provides diverse views on business problems that the team needs to solve, through their technical proficiency and experience in various areas such as backend, frontend, and infrastructure engineering.

They remove technical obstacles for the team, align company goals with team goals, and lead the team's business objectives. Furthermore, through skilled leadership, they foster a culture where team members can work with psychological stability and develop the overall capabilities of the team.

MLSE teams are developing specialized platforms and individual applications to provide services utilizing machine learning technology. Through these platforms, we enable other teams to easily integrate artificial intelligence (AI) into their services, secure competitive technical capabilities, and develop differentiated services.

The following describes the tasks performed by the Hyperconnect MLSE team, and the ML Software Engineering Team Leader will be responsible for managing a team that handles some of these tasks.

• Moderation Platform: A system that helps improve user experience by quickly reviewing and managing content.
• Labeling Platform: A system that classifies and tags data to create a format that machine learning models can learn from.
• Live Streaming Monitoring Platform: A system that monitors and manages live streams in real-time.
• On-device Machine Learning Model Platform: A system that supports running machine learning models directly on devices (e.g., smartphones, tablets).
• Recommendation System: A recommendation system that enhances user experience based on real-time user behavior pipelines.
• New AI Technology-based Products: Support for new products based on new AI technologies such as Gen AI.

Required Qualifications

• 5+ years of experience in software (backend, data pipeline, ML serving system, etc.) design, implementation, and operation.
• Solid fundamental knowledge of CS fundamentals (operating systems, computer system architecture, data structures, and algorithms).
• Proficiency in three or more of Java, Kotlin, Python, JavaScript, Go, and ability to learn and use other programming languages.
• Deep understanding of RDBMS.
• Strong communication skills to collaborate with stakeholders from various disciplines to deploy ML models into service.
• Experience leading an engineering team, with leadership and Team Management capabilities to help team members grow.
• Ability to communicate fluently in Korean, regardless of academic background or nationality.

Preferred Qualifications

• Experience from ML model training to service deployment.
• Experience developing and operating applications using the latest ML technologies (recommendation, generative AI).
• Experience integrating AI technology into actual services and significantly improving key metrics.
• Experience developing backend servers handling large-scale traffic.
• Understanding of distributed databases (RDBMS, DynamoDB, Cassandra).
• Experience developing distributed/parallel systems for large-scale/real-time processing (Spark, Flink).
• Proficiency in English.

Employment Type/Recruitment Process

• Employment Type: Full-time
• Recruitment Process: Document Screening > Coding Test > 1st Interview > Recruiter Call > 2nd Interview > 3rd Interview > Final Offer (*Additional interview stages may be conducted if necessary.)
• For document screening, only successful candidates will be notified individually.
• Application Documents: Detailed resume based on career, free format, in Korean or English (PDF).