Autonomous Driving Technical Lead

The Technical Lead will analyze complex and cross-functional issues within the Level 4 autonomous driving stack. This includes reviewing source code, architecture, logs, recorded sensor data, simulation results, test evidence, and vehicle behavior to distinguish between algorithmic, software, integration, calibration, timing, performance, hardware, interface, and data-quality issues.

Based on these analyses, the Technical Lead will develop and evaluate solution options considering technical feasibility, risks, dependencies, implementation effort, and overall system impact. Recommendations must be evidence-based and clearly documented. Where appropriate, prototypes or proofs of concept will be created to validate proposed approaches before contributing to their implementation, integration, and verification.

The role will provide technical direction by translating high-level objectives and identified issues into actionable engineering activities. This includes reviewing architecture decisions, algorithm choices, interfaces, implementation approaches, and development results with respect to robustness, functional coverage, performance, maintainability, and suitability for production use.

Technical risks, dependencies, inconsistencies, knowledge gaps, and engineering blockers must be identified early and driven toward sustainable resolution. Design reviews, code reviews, architecture discussions, and structured troubleshooting activities are therefore integral parts of the position.

Autonomous Driving and Physical AI Expertise

The role requires a strong understanding of the interaction between perception, localization, sensor fusion, prediction, behavior planning, motion planning, vehicle interfaces, and the underlying hardware and software platform.

Relevant technical areas include:

Point-cloud processing, occupancy grids, ground-plane estimation, and voxel-based representations

Object detection, classification, segmentation, tracking, and state estimation

Multi-modal sensor fusion across cameras, LiDAR, radar, GPS, and IMUs

Localization, SLAM, local-map generation, and HD mapping

Scene understanding, behavior modelling, maneuver classification, and trajectory prediction

Behavior planning, trajectory generation and optimization, collision checking, and decision-making under uncertainty

Machine-learning and deep-learning methods for autonomous systems, including transformer-based perception and occupancy networks

Relevant physical-AI approaches such as end-to-end and imitation learning, world models, vision-language-action models, and foundation models for driving and robotics

The Technical Lead will assess current research and industry developments and determine where emerging technologies can provide practical value to the production system. New approaches must be evaluated critically with regard to maturity, explainability, safety, integration effort, computational requirements, and operational benefit.

Software Development, Integration, and Validation

The position requires direct involvement throughout the software development lifecycle. The Technical Lead will work with existing architectures and codebases, implement or review production-grade software, and ensure that proposed solutions can be integrated into the overall autonomous driving system.

The role will contribute to meaningful test scenarios, technical acceptance criteria, and validation approaches. Defects identified during software, simulation, system, hardware, or vehicle integration must be analyzed systematically and traced to their technical causes.

Relevant environments and activities may include:

SIL, MIL, PIL, HIL, vehicle-in-the-loop, and on-vehicle testing

CARLA, LGSVL, or comparable simulation environments

ROS bag, PCAP, and sensor-data replay

Automated regression testing and CI/CD pipelines

Closed-loop scenario evaluation

Calibration and time-synchronization analysis

Fault-injection, stress, and robustness testing

CPU and GPU performance analysis

The Technical Lead will contribute to integration and release-readiness assessments by evaluating functional behavior, interfaces, performance, edge-case coverage, and remaining technical risks. Suitable KPIs will be defined or reviewed for perception accuracy, prediction and planning quality, latency, resource consumption, robustness, and overall system stability.

Technical Collaboration

As a central technical interface across the participating engineering organizations, the Technical Lead will establish a detailed understanding of the existing stack, architecture, development environment, operational constraints, and current technical challenges.

The role facilitates the exchange of technical knowledge and aligns objectives, interfaces, assumptions, dependencies, and solution approaches with the relevant specialists. Technical workshops, design and architecture reviews, code reviews, and troubleshooting sessions will be used to establish a shared technical understanding and translate decisions into actionable engineering guidance.

Periodic on-site collaboration and vehicle testing in Fribourg, Switzerland, form part of the role.