Develop unified computer vision models for autonomous driving, spanning 3D perception and multi-task learning, while optimizing distributed training and improving model robustness through regression analysis and self-supervised learning.
42dot jobs
42dot is Hyundai Motor Groupβs global software center, developing software-defined vehicle and mobility technologies.
80 open roles at 42dot
Leads workplace food and beverage operations, from strategy, budgets, and vendor selection to data-driven improvements, service design, compliance, and employee-focused dining experiences.
Shape OEM and market needs into commercially viable product roadmaps, offerings, pricing, and business models for SDV and AI mobility products, guiding commercialization and market expansion.
Own software and new-vehicle quality assurance across development and early production, using APQP, customer issue analysis, and cross-functional improvement to prevent defects and improve IVI and AI service quality.
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Develop and optimize Navigation Agent models by fine-tuning LLMs, building machine learning components, and improving evaluation, data quality, and real-world service performance.
Own the strategy and definition of a shared mobility data platform, translating vehicle and product use cases into reusable data, context, and interface requirements and validating them with product teams.
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Design and optimize LLM training pipelines across pre-training and post-training, improving training efficiency and generation quality while developing self-refining learning structures for production-ready language models.
Design and develop speech recognition and wake word detection models, build speech datasets, and deliver optimized batch and streaming applications for server and on-device environments.
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Develop Android-based in-vehicle camera systems by integrating Camera3 and EVS HALs, connecting remote video streams to the camera framework, and building camera applications such as dash cams and surround view.
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Develop vehicle security for software-defined vehicles, including OP-TEE and HSE features, secret and key lifecycle management, secure boot, firmware integrity checks, and security testing.
Develop multimodal VLA-style driving models that connect visual perception, scene context, and driving actions to improve planning, decision-making, and real-world autonomous driving behavior.
Evaluate autonomous driving and ADAS features in real-world and simulation environments, develop scenario-based tests, analyze performance and issues, and work with development teams to improve system safety and reliability.
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Research and develop unified computer vision models for autonomous driving, spanning 3D perception, multi-task and distributed training, regression analysis, and self-supervised visual representation learning.
Operate and optimize large-scale GPU infrastructure across multiple data centers, maintaining high availability, automating operations, and supporting distributed training for autonomous driving models.
Leads end-to-end design strategy for in-vehicle and connected mobile experiences, shaping intuitive user journeys, design systems, and product decisions in collaboration with cross-functional teams.
Design, implement, and validate autonomous-driving systems or in-vehicle AI agents, using real-vehicle data, simulation, and production systems to turn research into deployable mobility technology.
Own the organizationβs open-source governance strategy and compliance program, establishing policies, workflows, tools, and training to manage OSS use, licensing, and legal and quality risks.
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