Senior Simulation & Synthetic Data Generation Engineer – Self-Driving

VinFast; Frankfurt; Vor Ort; EUR 70.000 - 90.000; Vollzeit

Zusammenfassung

A pioneering electric vehicle company in Frankfurt is looking for a Senior Simulation & Synthetic Data Generation Engineer. You'll research and develop advanced techniques in computer vision and machine learning to generate high-quality data for self-driving technology. Responsibilities include implementing data generation pipelines, collaborating with cross-functional teams, and applying generative modeling techniques. This position offers an opportunity to work with industry-leading professionals in an innovative and dynamic environment.

Qualifikationen

• 5+ years of industry experience in computer vision, graphics, or ML.
• Strong background in developing ML pipelines incorporating synthetic data.
• Experience with large-scale data pipelines and distributed training.

Aufgaben

• Design and implement generative AI-driven pipelines for synthetic data.
• Collaborate with teams to integrate synthetic data into workflows.
• Research and apply methods in computer vision and generative modeling.

Kenntnisse

Computer vision

Machine learning

Computer graphics

Python

C++

Ausbildung

MSc/PhD in Computer Science or related field

Tools

PyTorch

TensorFlow

CARLA

Gazebo

Jobbeschreibung

Senior Simulation & Synthetic Data Generation Engineer – Self-Driving

Frankfurt am Main, Germany | Posted on 11/06/2025

VINFAST is a pioneering electric vehicle (EV) company committed to revolutionizing the automotive industry with sustainable and innovative mobility solutions. As a leading player in the EV market, VinFast is dedicated to delivering high-quality, cutting‑edge electric vehicles that redefine the driving experience. Our team consists of passionate professionals driven by a shared vision of creating a greener and more sustainable future through innovation, technology, and excellence.

Synthetic data and simulation are critical to scaling self-driving technology. In this role, you will research, develop, and deploy state‑of‑the‑art techniques in computer graphics, computer vision, and machine learning to generate high-quality data for training and validating the self-driving stack. You will help shape the future of synthetic data generation pipelines and simulation frameworks, enabling new sensing model capabilities and accelerating development of safe autonomous vehicles.

• Design and implement generative AI–driven pipelines for synthetic data generation, including 3D scenes, sensor simulation, and realistic traffic scenarios.
• Develop synthetic datasets to train and validate perception and sensing ML models, ensuring diversity and realism across scenarios.
• Collaborate with perception, prediction, mapping and planning teams to integrate synthetic data into model training and evaluation workflows.
• Research and apply advanced methods in computer vision, computer graphics, and generative modeling (e.g., diffusion models, NeRF, Gaussian splatting).
• Benchmark and validate synthetic data against real-world distributions, ensuring effectiveness in closing domain gaps.
• Build scalable infrastructure for large-scale synthetic data generation and management.
• Work closely with other engineering and research experts to align synthetic data strategy with broader ML and autonomy goals.
• Look for high-impact findings and propose improvements to synthetic data pipelines that unlock new model capabilities.

Requirements

• MSc/PhD in Computer Science, Computer Graphics, Robotics, or a related field with 5+ years of industry experience.
• Strong background in computer vision, computer graphics, or machine learning.
• Experience developing ML pipelines that incorporate synthetic or simulated data.
• Proficiency in Python and C++ with experience in ML frameworks such as PyTorch or TensorFlow.
• Familiarity with 3D graphics frameworks, game engines, or robotics simulators (e.g., CARLA, Gazebo).
• Knowledge of generative modeling techniques (e.g., diffusion models, GAN, NeRF, Gaussian splatting, etc.).
• Experience with large-scale data pipelines, distributed training, and evaluation frameworks.
• Strong problem-solving skills, creativity, and ability to work across cross‑functional teams.
• Opportunity to collaborate with and learn from industry-leading professionals in the automotive domain.

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