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42dot

Unified platform for multi-modal urban mobility

AI Engineer - Personalized & Proactive Agent

Applied Machine LearningConfirmed live in the last 24 hours
Full-timePangyo-ro, Bundang-gu, Seongnam-si, Gyeonggi-do, South KoreaNo salary listedHybrid

About the Job

Requirements

  • A master's degree or higher in computer engineering, artificial intelligence, or a related field, and at least four years of professional experience in AI/ML or software engineering.
  • Understand the core principles of LLMs and agentic AI and have experience applying them in production services.
  • Have experience analyzing real-user logs and data to identify problems and derive improvement priorities.
  • Be able to structure and improve uncertain problems through hypothesis formation, experimentation, and evaluation.
  • Have software development capabilities to design, implement, and operate production-level AI/ML systems; Python or Kotlin is preferred.
  • Be able to define important problems independently, take ownership of outcomes delivered to users, and collaborate effectively.

Responsibilities

  • Build long-term memory, retrieval, personalization systems, and learning loops that learn from and use user experience, preferences, and context from interactions.
  • Design context engineering and context summarization strategies to select and compress memories and context within limited context-window and latency constraints.
  • Develop proactive agent experiences that recommend places and media by generating and ranking candidates based on preferences, routines, schedules, location, and driving context, and provide conversations, notifications, reminders, and briefings at appropriate times.
  • Design offline evaluations and online A/B experiments to verify the effects of personalization and proactive intervention; define quality and impact metrics and build a closed-loop evaluation system to continuously improve memory, recommendations, and intervention policies.
  • Experiment with relevant research and technologies, select and combine LLMs, machine-learning and statistical models, and rule-based systems according to the problem, and implement them as stable production capabilities.

Desired Qualifications

  • Research or development experience with long-term memory, retrieval, user modeling, personalization, or recommendation systems.
  • Experience developing context-aware or proactive assistants using context signals such as schedules, locations, and movement patterns.
  • Experience building data pipelines that extract explicit and implicit feedback from user interaction data and connect it to user profiles or features.
  • Experience experimenting with and optimizing recommendation and proactive intervention policies using ranking, contextual bandits, or sequential decision-making methods.
  • Experience directly training and deploying LLMs through mid-training or post-training, or machine-learning models such as recommendation or ranking models.
  • Experience combining on-device AI with cloud AI, or applying privacy and sensitive-information handling principles to a product.
  • Experience evaluating and optimizing AI/LLM system quality, intervention timing, latency, cost, and reliability.

About the Company

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42dot

Unified platform for multi-modal urban mobility

42dot.ai provides a platform called UMOS (Urban Mobility Operating System) that connects and manages multiple transportation modes—such as cars and drones—within a single system for cities, agencies, and private clients. UMOS enables efficient transportation management, demand-response services, and smart logistics by integrating data and operations across modes, powering operations through a subscription-based platform-as-a-service model. Unlike single-mode solutions, 42dot.ai offers multi-modal, city-focused orchestration that bridges public, private, and logistics needs. The company aims to transform urban mobility by helping cities run more efficiently, cut costs, and improve the experience for commuters and logistics providers.

Company size
501-1,000
Company stage
Growth Equity (Venture Capital)
Total funding
$731.9M
Headquarters
Seoul, South Korea
Founded
2019

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