AI Engineer (Agent) - Join Our Innovative Team at 42dot

Join Our Team of Innovators!About 42dotAt 42dot, our Gleo Core team is dedicated to advancing the core technologies of LLM and Agent systems applied in Gleo AI. Gleo is designed to facilitate natural and friendly conversations within vehicles, accurately processing user requests while offering a personalized experience through memory. We are on the lookout f…

Autonomous Driving EngineeringAt 42dot, we are pioneering the development of camera-based, end-to-end autonomous driving software and high-performance, low-power embedded systems. We've established an advanced MLOps infrastructure that automates our data pipelines, enabling rapid iterations from AI model training to real-world validation. Our autonomous driving technology, 'Atria AI', is set to be implemented in mass-produced vehicles with Level 2+ autonomy by the end of 2027.Join us for a unique opportunity to engage with camera-based end-to-end autonomous driving and Physical AI, contributing to next-generation algorithms based on VLA. We are looking for tenacious and proactive individuals ready to change the world!Role OverviewThis position is for a full-time transition internship (MS/PhD), focusing on connecting research outcomes to practical autonomous driving systems through hands-on development and research.During the internship, you will not just assist but actively engage in product development aimed at mass production. You will work within a cutting-edge research team, defining and solving problems using real vehicle data, production-level code, and MLOps systems. You will undertake technical challenges equivalent to full-time engineers, gaining invaluable experience linking research with practical implementations.What You'll DoDesign, implement, and validate core technologies for autonomous driving systems end-to-end.Develop and validate algorithms/models based on real vehicle data.Analyze and enhance performance through simulations and real-world experiments.Implement research findings into practical systems.Collaborate closely with production teams to solve real-world challenges.Available TracksYour role and department will be determined based on your expertise, research interests, and career aspirations assessed during the internship and interview process.[Physical AI]Implementation and experimentation of perception and behavior prediction ML models for autonomous driving.Preprocessing driving data and organizing/analyzing training datasets.Evaluation of model performance and analysis of experimental results.Consolidation of failure cases and experimentation for performance enhancement.[Sensor Fusion]Implementation of object-level fusion and tracking using results from cameras and other sensors.Performance analysis and log analysis based on real vehicle data.Understanding and improving fusion logic structures in C++ based real-time systems.[SLAM]Research and development of SLAM and localization algorithms for autonomous driving.Basic location estimation and map creation using sensor data from cameras and IMUs.Accuracy and stability analysis based on real or simulated data.[AI Infrastructure]Development of AI infrastructure to support autonomous driving systems.

Join 42dot as a Security Engineer specializing in vehicle networking. In this role, you will be a key player in developing and implementing robust security solutions for our cutting-edge automotive technologies. Your expertise will help safeguard our systems against emerging threats and vulnerabilities.Responsibilities include conducting security assessments, developing security protocols, and collaborating with cross-functional teams to enhance our vehicle networking infrastructure. You will leverage your knowledge of security principles and best practices to innovate and protect our products.

42dot is looking for an Infra Security Engineer to focus on endpoint security solutions at the Software Dream Center in Pangyo, South Korea. This position centers on both implementing and managing security measures designed to protect the company’s infrastructure. Role overview This role involves developing security strategies that strengthen the organization’s defenses. The main focus is on endpoint security, ensuring that all devices connected to the network are protected against threats and vulnerabilities. Key responsibilities Implement endpoint security solutions across the company’s infrastructure. Manage and maintain these security systems to ensure ongoing protection. Develop strategies to improve cybersecurity resilience and address emerging risks. Location This position is based in Pangyo at the Software Dream Center, South Korea.

Join Our Innovative Team!As an LLM Engineer specializing in Reinforcement Learning at 42dot, you will design and implement advanced learning pipelines to develop generative language models for real-world applications. You will continuously experiment with novel methodologies to enhance service quality, ensuring that our language models not only meet user needs but also autonomously improve their performance.Key ResponsibilitiesOptimize the efficiency of the LLM training process using algorithms such as Direct Alignment, PPO, GRPO, and DPO.Enhance the accuracy and stability of generated outputs by designing learning structures that prevent reward hacking and facilitate self-refinement.Develop foundational models that integrate seamlessly with external knowledge and APIs, enabling the LLM to autonomously select necessary tools based on the type of instructions.

Join Our Innovative Team!At 42dot, our IVI OS Engineers play a crucial role in enhancing the In-Vehicle Infotainment (IVI) system, a core component of Software Defined Vehicles (SDV). Leveraging Android Automotive, you will optimize and develop essential middleware and applications that drive our competitive edge in the automotive industry.Your ResponsibilitiesDevelop Android Automotive HAL, including Vehicle, GNSS, and Sensor HAL.Create vehicle data simulation tools based on Android Automotive OS.Integrate IVI with SDV Vehicle OS and develop service applications.QualificationsExperience in developing embedded systems based on AAOS/Linux.Proficient in Android HAL development and testing with VTS.Software development experience utilizing protocols like CAN, SOME/IP, or DDS.Strong skills in embedded system languages such as C, C++, Java, or Rust.Preferred QualificationsBroad understanding of Android platform and Automotive Car Services.Experience integrating IVI with vehicle controllers.Familiarity with UDS-based vehicle controller diagnostics.Interest in code automation and efficiency improvements.Interview ProcessApplication screening - Coding test - Video interview (approx. 1 hour) - Face-to-face or video interview (approx. 3 hours) - Final acceptance.The process may vary by position and is subject to change based on circumstances.Interview schedules and results will be communicated via the email provided in your application.Additional InformationPlease exclude personal information such as your Social Security number, family relations, marital status, salary information, photographs, physical condition, and region of origin when submitting your resume.All submitted files should be in PDF format and under 30MB. If you encounter issues during the upload process, please send your resume to recruit@42dot.ai along with the URL of the position you are applying for.A reference check may be conducted with the applicant's consent after the interview process.Veterans and individuals protected by employment protection laws are given preference according to relevant laws.Applicants holding a disability registration certificate are preferred in accordance with the Act on the Promotion of Employment for Disabled Persons and Vocational Rehabilitation.42dot does not accept unsolicited resumes from search firms and will not pay a fee for resumes submitted without a prior agreement.※ Please review the following information before applying.Learn about how 42dot works, here.

Join Our Innovative Team!The Audio Team at 42dot is dedicated to developing cutting-edge voice technologies that enhance user interaction with vehicles. Our voice recognition technology enables seamless communication between users and their vehicles through voice commands, making driving safer and more convenient.Key ResponsibilitiesDesign and develop speech-to-text (STT) acoustic and language models, along with building comprehensive voice databases.Design wake word detection (WWD) models and establish related voice databases.Create and optimize batch and streaming voice applications for server and on-device environments (Linux, Android).Develop and optimize hardware-efficient models.QualificationsMinimum of 2 years of relevant experience (new graduates with a master’s degree are welcome to apply).Strong foundational knowledge in speech signal processing.Research experience in machine learning/artificial intelligence related to STT or WWD technology.Ability to develop applications on edge devices (Linux, Android).Proficient programming skills for innovative technology solutions (C/C++/Python/Shell).Experience with open-source deep learning frameworks (e.g., PyTorch, TensorFlow, Keras, Caffe).Preferred QualificationsFamiliarity with version control systems (Git).Understanding of unit testing, static analysis, test automation, and CI/CD processes.Experience in developing STT technologies for commercial applications.Research experience in self-supervised learning (SSL) and attention-based encoder-decoder (AED) STT models.Experience in multilingual STT research.Research experience in language models for speech recognition.Author of publications in top-tier journals/conferences in speech recognition/machine learning/AI.Possession of a master's or doctoral degree in relevant fields.Interview ProcessApplication review - Coding test - Video interview (approximately 1 hour) - In-person or video interview (approximately 3 hours) - Final selection.The process may vary by role and is subject to change based on scheduling and circumstances.Interview schedules and results will be communicated via the email provided in your application.Additional InformationPlease refrain from including prohibited information such as personal ID numbers, family relations, marital status, salary expectations, photographs, physical conditions, or place of origin in your resume.All submitted files should be in PDF format and less than 30MB. If you encounter issues uploading your resume, please send it along with the URL of the position you're applying for to recruit@42dot.ai.

Join Our Innovative Team!At 42dot, we are at the forefront of developing an AI Assistant App that enhances the driving experience by minimizing unnecessary interactions and allowing for secure, voice-controlled vehicle management. Our team is dedicated to creating intuitive solutions powered by Large Language Models (LLM), delivering only the most relevant information to drivers while ensuring they can access smart services effortlessly through voice commands.We continually research and develop personalized services that adapt to the user's context within the vehicle's infotainment (IVI) environment, leveraging both vehicle and driver data to provide a smarter voice experience.Key ResponsibilitiesDevelop Android applications tailored for vehicles, utilizing cutting-edge AI SDKs including voice recognition and synthesis.Customize user experience (UX) and HMI integration in alignment with Google Automotive Services (GAS) and AAOS specifications.Integrate vehicle control features (e.g., air conditioning, windows, seats) through the AAOS Vehicle API.Create services that interface with existing IVI applications for navigation, telephony, and radio.Design and develop interfaces for LLM-based third-party application integration.QualificationsA minimum of 3 years experience in Android application development (including graduate studies).Strong understanding of the Android platform with proficiency in Java or Kotlin.Proficient in at least one of the following languages: Java, Kotlin, or C++.Preferred QualificationsExperience in developing vehicle infotainment (IVI) or connected vehicle services.Knowledge of AAOS (Android Automotive OS) or AOSP (Android Open Source Project) development.Experience utilizing modern architectures and communication technologies such as MVVM, RxJava, gRPC, and RESTful APIs.Proven track record of enhancing app performance and user experience based on user feedback.A collaborative spirit with a passion for sharing technical knowledge and learning new technologies.Portfolio submission (e.g., GitHub contributions) is a plus.Interview ProcessApplication review - Coding test - Video interview (approx. 1 hour) - In-person or video interview (approx. 3 hours) - Final selection.Process may vary by position and is subject to change based on scheduling and circumstances.Interview schedules and outcomes will be communicated via the email provided in your application.Additional InformationPlease exclude sensitive information such as personal ID numbers, family relations, marital status, salary history, photos, physical characteristics, and place of origin from your resume submission.All submitted files should be in PDF format and under 30MB. If you encounter issues uploading your resume, please send it to recruit@42dot.ai along with the position URL.Post-interview, reference checks may be conducted with your consent.

Join Our Team of InnovatorsAt 42dot, we are searching for a highly skilled Perception Team Lead to take charge of the core perception technologies essential for autonomous vehicles. You will leverage advanced computer vision and machine learning techniques to interpret visual data from various sensors, including cameras and LiDAR, to design and implement an autonomous perception system that achieves human-level reliability and scalability.This position not only defines the technological direction and roadmap but also involves hands-on leadership in developing core perception algorithms and systems. As a technical leader, you will be responsible for ensuring the technical excellence of the team and mentoring team members to foster their growth.About 42dot42dot is a pioneering mobility AI company dedicated to solving mobility challenges through software and AI. As part of the Hyundai Motor Group's global software center, we are at the forefront of developing software-defined vehicles and shaping the future of mobility.We prioritize safety and develop user-centric software-defined vehicle technologies that provide continuous updates for optimal performance, akin to a smartphone experience. By advancing software and AI technologies, 42dot envisions a new world through an autonomously managed urban traffic operation system where everything is interconnected and moves autonomously.Key Responsibilities1. Technical and Architectural Leadership- Establish and guide the technical roadmap for perception/computer vision technologies for autonomous driving- Actively participate in the design, validation, and enhancement of algorithms based on 3D computer vision and machine learning- Design scalable and robust perception system architectures considering large datasets and real-world environments- Lead the transition from research to production for applying research findings to actual products/platforms- Drive technical decision-making and problem-solving for performance, latency, and stability issues.2. Core Technology Areas- Object detection, pose estimation, tracking, and motion understanding- Multi-sensor perception (Camera, LiDAR, Radar, GPS, IMU, etc.)- Efficient and scalable vision systems for real-time autonomous driving- Vision-based robotics and physics-based/low-level vision approaches- Algorithm and system optimization considering performance, latency, and stability3. Team and Project Leadership- Lead technical decision-making and reviews for core code, algorithms, and research within the perception team- Mentor team members to support their technical growth- Collaborate closely with related teams in product, systems, robotics, and vehicle platforms- Manage project schedules, priorities, and identify as well as resolve risks.QualificationsMinimum 8 years of relevant industry experience or equivalent research/development experience (PhD preferred)Deep theoretical understanding and practical application experience in computer vision and machine learningProficient programming skills in large codebases (C/C++, Python, etc.)Leadership and communication skills to structure complex problems and make technical decisionsPreferred QualificationsExperience leading Perception/AI systems in autonomous driving or roboticsExperience in developing multi-sensor based perception systems (Camera, LiDAR, Radar, GPS, IMU, etc.)Experience with real-time systems, parallel programming, and performance optimizationDevelopment experience related to VR/AR or 3D graphics/simulation; publication, patents, open-source contributions, or academic activity history (CVPR, ICCV, ECCV, IJCV, TPAMI, TIP, etc.)Interview ProcessInitial phone screening followed by technical interviews and team fit discussions.