Turing株式会社のEN_3015_Simulation Engineer (End-to-End Autonomous Driving Model Development)の求人

-About the role-
◆This role is open to engineers with expertise in the simulation domain.◆

Turing is a deep-tech startup on a mission to achieve full self-driving.

To accelerate research and development of our End-to-End autonomous driving model, we are building next-generation simulation technology. Specifically, we are combining a 3D Gaussian Splatting-based simulator for evaluation and training, a large-scale distributed training infrastructure, and control systems (such as MPC) to enable efficient and robust autonomous driving development that is not dependent on real-vehicle testing.

The Simulation Engineer in this role will lead the design and development of the closed-loop simulator that forms the foundation of this effort, working closely with ML engineers to accelerate the advancement of autonomous driving technology.

■What you will work on
-Development of a 3DGS-based closed-loop simulator
-Support for End-to-End autonomous driving model development
-Integration with distributed training infrastructure

■Goal of simulator development
We will build a high-fidelity simulation environment that leverages large-scale generated 3DGS scenes to enable training and evaluation of End-to-End models.
We aim to integrate control layers and physical simulation to create an environment where control algorithm exploration can be conducted without relying on real-vehicle testing.

■What does "model development support" mean?
We will support pretraining of E2E models suited for reinforcement learning and imitation learning, and drive efficient E2E model exploration including the control layer.

■Integration with distributed training infrastructure
We will expand our simulation environment to support robust model training across diverse traffic scenarios and randomized physical properties. To make the simulation environment a shared infrastructure usable across the entire company, it needs to connect seamlessly with our existing model development data pipeline and training infrastructure.
Rather than simply building a simulator, we aim to establish it as a company-wide common platform that supports model development across all teams.

■Who we are looking for
・Driven to build a world-class company
・Self-starter who takes initiative on everything
・Humble, with genuine empathy for others
・Flexible and excited by rapid organizational and business growth
・Growth-oriented mindset
・Resilient — able to find joy even in tough challenges

◆Tech stack
・Language：Python、C++
・Libraries：PyTorch、OpenCV、MMDetection、ONNX、TensorRT
・Middleware：Slurm、Ray
・Cloud：AWS、Databricks (DWH)
・Platform：Jetson、Linux

【LEARN MORE】
▼Company website
https://tur.ing/

▼Turing Tech Blog
https://zenn.dev/p/turing_motors

▼Turipo（Owned media / Web Magazine）
https://tur.ing/turipo

▼Turing Tech Talk #27 From Digital to the Real World: The Path to Full Self-Driving Through Reinforcement Learning
https://www.youtube.com/live/atAd0hHMwwI?feature=shared

【Application notes】
· Please submit your resume and work history in PDF format.
· Do not include salary information (current or desired) in your application documents or entry form.
· Our HR team will discuss compensation separately during the selection process.

■Required qualifications
・Alignment with Turing's mission and values
・Software development experience using Python and/or C++
・Knowledge and practical experience in at least one of the following: simulation, robotics, or graphics
・Problem-solving ability for technical challenges and strong collaborative skills
・Japanese language proficiency (JLPT N2 or equivalent)

■Preferred qualifications
・Experience with cutting-edge 3D graphics technologies such as Gaussian Splatting or NeRF
・Experience developing with game engines (Unreal Engine, Unity, etc.) or rendering systems
・Experience developing large-scale systems or real-time applications
・Experience with autonomous driving or in-vehicle system development
・Experience with sensor simulation (LiDAR, radar, cameras, etc.)
・Knowledge of rigid body simulation or physically-based rendering
・Experience designing and optimizing large-scale ML inference systems or GPU cloud environments
・Development experience in cloud environments (AWS, GCP, Azure, etc.)