[We Are A Mobility AI Company] 42dot은 소프트웨어와 AI 기술로 service-defined과 safety-designed 가치를 중심으로 한 SDV (software-defined vehicle)를 만들고 있습니다. 2022년 8월 현대자동차그룹의 소프트웨어 관련 사업 역량을 강화하는 목표로 그룹의 멤버가 된 42dot은 SDV 기술을 기반으로 자율주행 및 모빌리티 솔루션과 서비스를 제공하고 있습니다. [42dot 기사]

https://www.hankyung.com/article/202401118201g

[42dot 영상]

https://www.youtube.com/watch?v=KX5FVReOdNg

https://www.youtube.com/watch?v=xL56nsH585s

[We are looking for the best] At 42dot, our Senior Machine Learning Engineer team focuses on developing state-of-the-art solutions in Motion Planning algorithms. We create advanced prediction algorithms for future path planning, a critical aspect of ensuring the safety and reliability of autonomous driving systems. By utilizing vast datasets, we conduct comprehensive analyses of driving patterns, allowing us to design algorithms that facilitate smooth and natural vehicle control. Our goal is to drive the innovation needed to shape the future of autonomous driving technologies.

• Lead the design and development of advanced machine learning models for autonomous driving tasks, including perception, decision-making, and control • Drive end-to-end machine learning pipeline development from data collection and preprocessing to model training, optimization, and deployment • Apply state-of-the-art deep learning techniques, such as reinforcement learning, imitation learning, and self-supervised learning, to improve autonomous driving performance • Optimize model performance in real-world driving conditions and ensure seamless integration with the vehicle’s software stack • Collaborate with cross-functional teams, including software, hardware, and vehicle control, to align machine learning systems with overall vehicle architecture • Mentor junior engineers and guide best practices for machine learning development • Stay updated on the latest trends and research in machine learning and autonomous driving, bringing innovative approaches to the team

• Master’s or Ph.D. in Computer Science, Machine Learning, AI, Robotics, or a related field • Extensive experience with deep learning algorithms (CNN, RNN, Transformer) and their applications in autonomous systems • Strong proficiency in Python and machine learning frameworks (TensorFlow, PyTorch), with a proven track record of deploying models in real-world systems • Deep understanding of reinforcement learning, imitation learning, and advanced optimization techniques • Experience working with large-scale datasets and cloud-based machine learning pipelines • Excellent leadership and communication skills, with a demonstrated ability to lead technical projects

• Strong background in autonomous driving technologies and end-to-end learning for self-driving cars • Experience with hardware-in-the-loop (HIL) testing and real-time deployment • Experience in research and development related to autonomous driving and robotics • ROS1/ROS2 experience • Experience deploying predictive models in real-world environments • Inference optimization experience (TensorRT, CUDA programming, etc.) • History of books/academic activities in related fields (CVPR, ICCV, ECCV, IROS, ICRA, etc.)

• Application Review - 1st interview - 2nd interview - 3rd interview - Offer Negotiation - Hiring • Screening procedures may be operated differently for each job and may vary depending on the schedule and situation. • The screening schedule and results will be notified individually by email registered on the application form.

• 이력서 제출 시 주민등록번호, 가족관계, 혼인 여부, 연봉, 사진, 신체조건, 출신 지역 등 채용절차법상 요구 금지된 정보는 제외 부탁드립니다. • 인터뷰 프로세스 종료 후 지원자의 동의하에 평판조회가 진행될 수 있습니다. • 국가보훈대상자 및 취업보호 대상자는 관계법령에 따라 우대합니다. • 장애인 고용 촉진 및 직업재활법에 따라 장애인 등록증 소지자를 우대합니다.