Tìm việc làm IT

Overview: As the Director of Data Pipeline & Simulation, you will lead the development of large-scale data infrastructure, simulation technologies, and validation frameworks that support the continuous improvement and safe deployment of our autonomous driving systems. You will define the technical vision, build and lead multidisciplinary teams spanning autonomy data platforms, neural simulation, HD mapping, and system evaluation. Working closely with our end-to-end driving, platform, integration, and safety teams, you will establish a scalable data flywheel that transforms real-world fleet data into high-quality training datasets, realistic simulation environments, and rigorous validation evidence. This is a senior technical leadership role with ownership of the data and simulation ecosystem, as well as independent evaluation and release readiness of autonomous driving models. Responsibilities Own the technical vision and roadmap for end-to-end driving and behavior modeling: which architectures, which training paradigms, which data, in which order, and revise it as the field and the fleet data change. Build and run the large-scale training operation: the loop that takes a continuously growing stream of fleet data through curation, training, evaluation and release on a regular cadence. Hire and lead team leads and engineers; set the standards for experiments, reviews, model cards and release readiness. Oversee progress across different teams with real technical depth. Decide, with the Safety & Evaluation lead, what "better" means before each training cycle, and accept the gate's verdict when it says a model is not ready. Report program status, risks, budget and headcount to the Division Director. Requirements 8+ years in data-intensive AI systems, with 5+ years leading multi-team organizations (20+ engineers) that built and ran the data side of a shipped AI product. Hands-on, proven experience owning an AI data lake and data pipeline at scale: ingestion from a continuous source (a fleet, a device population, a user base), petabyte-scale storage and processing, dataset curation and versioning, labelling operations, data quality and lineage, and the engineering that keeps the pipeline reliable as volume grows ten-fold. At least one data-driven AI product you led to successful deployment, where a data flywheel - mining, curation, labelling, retraining, evaluation - improved the product after launch. Autonomous driving is strongly preferred but not required; large-scale recommendations, speech, vision, mapping or foundation-model data operations all count. Technical depth across data mining and active learning, auto-labelling with offline models, neural rendering or simulation, closed-loop evaluation and statistical validation. Expert in at least two. Experience defining release criteria or quality gates for an ML system in production, and holding them under schedule pressure. A clear view on how data engines, learned simulators and evaluation will evolve over the next five years, and the judgment to choose what to build now versus later. Experience as a technical manager: hiring senior leads, running vendors, managing budget, compute and storage cost. M. S. or Ph. D. in computer science, machine learning, robotics or a related field, or equivalent track record; fluent English With respect to all your personal data shared to VinFast in the application and the entire recruitment process of VinFast, by clicking “Apply”, submitting your resumé/CV and/or participating in VinFast's recruitment process, you agree that you have read VinFast's Personal Data Protection Policy ("Policy") posted at https://vinfastauto.com/vn_vi/dieu-khoan-phap-ly or https://vinfast.vn/privacy-policy/, you agree to the Policy and consent for VinFast to process your personal data in accordance with the Policy and the applicable regulations on personal data protection. To all recruitment agencies: VinFast does not accept agency resumes. Please do not forward resumes to our careers alias or other VinFast employees. VinFast is not responsible for any fees related to unsolicited resumes.