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Location
In office (Hanoi)
Seniority
Middle · 3+ years exp
Employment
Full-Time

Confirmed on the employer's own hiring board on Nov 12, 2026. First seen by Alion on Nov 12, 2026. VinFast scores B on the Alion truth index.

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VinFast is a Vietnamese electric vehicle maker within the Vingroup conglomerate that designs and builds electric cars, e-scooters and motorbikes, buses, and charging and battery swap infrastructure, with its main manufacturing complex in Haiphong. Founded in 2017, it listed on the Nasdaq in 2023 through its Singapore-registered parent and sells vehicles in Vietnam, North America, Europe, India and Southeast Asia. It hires AI, embedded, AUTOSAR, sensor fusion and test engineers, data scientists, powertrain and quality engineers, and purchasing and logistics leaders, mostly in Hanoi and Haiphong.
Overview As a Software Engineer specializing in Map Pipeline & Automation, you will develop scalable data pipelines and automated workflows that transform raw sensor data and external map sources into reliable, high-quality maps for autonomous driving. Working closely with mapping, perception, and autonomous driving teams, you will build tools for map processing, validation, versioning, and deployment. This role offers the opportunity to work with large-scale geospatial data, distributed computing infrastructure, and modern software engineering technologies to support the development and continuous improvement of our autonomous driving systems.

Responsibilities Develop and maintain automated map production pipelines, covering data ingestion, alignment, map conflation, format conversion, validation, packaging, and release. Build automated map validation tools to detect geometric inconsistencies, topology errors, connectivity issues, and missing or incorrect map attributes. Develop scalable map storage and retrieval services, including map indexing, tile serving, lane-level queries, and APIs for autonomous driving applications. Implement map format conversion and export tools, supporting industry-standard formats such as OpenDRIVE and Lanelet2 for simulation, planning, and evaluation. Build robust data processing workflows for integrating vehicle sensor logs, HD maps, and third-party geospatial datasets. Improve map pipeline reliability and efficiency through automated testing, monitoring, CI/CD, and infrastructure automation. Develop visualization and debugging tools to support map inspection, quality assessment, and investigation of mapping errors. Collaborate with mapping, perception, simulation, and autonomous driving teams to integrate map data and services into training, testing, and deployment workflows. Explore ML-assisted map automation techniques, including lane extraction, traffic sign detection, map change detection, and automated map updates. Contribute clean, efficient, and maintainable code to shared mapping infrastructure, processing pipelines, and development tools. Requirements 3+ years of practical experience in software engineering, data engineering, robotics, geospatial computing, or related fields. Bachelor's or Master's degree in Computer Science, Robotics, Software Engineering, or a related discipline, or equivalent practical experience. Strong programming skills in Python and C++, with experience developing reliable data processing pipelines and backend services. Solid understanding of software engineering fundamentals, including data structures, algorithms, system design, and automated testing. Experience with Linux-based development environments, containerization technologies such as Docker, and workflow orchestration tools. Familiarity with cloud computing, distributed data processing, or scalable storage infrastructure. Experience working with relational databases, geospatial databases, or large-scale structured datasets. Familiarity with developing and maintaining backend services and APIs using REST or gRPC. Good analytical and problem-solving skills, with the ability to debug complex data workflows and improve system performance. Ability to collaborate effectively with researchers and engineers in a fast-paced R&D environment.

Preferred

Qualifications Experience with geospatial data processing, coordinate reference systems, or HD map representations. Familiarity with autonomous driving map formats and tools such as Lanelet2, OpenDRIVE, or similar frameworks. Knowledge of LiDAR point cloud processing, SLAM, pose estimation, or pose-graph optimization. Experience developing automated map validation, map conflation, or map change detection pipelines. Familiarity with GIS tools and geospatial libraries such as PostGIS, GDAL, or similar technologies. Experience with distributed computing, cloud infrastructure, and workflow orchestration frameworks. Knowledge of machine learning approaches for lane detection, road topology estimation, or automated map generation. Familiarity with frontend technologies such as React or TypeScript for building internal visualization and debugging tools. Experience with autonomous driving, robotics, navigation, or simulation systems. Understanding of map versioning, continuous map updates, and data quality management for autonomous driving. 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.

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