Autonomous Driving Technical Lead

Luxoft; Schweiz; Hybrid; EUR 90,000 - 140,000; Full time

Job summary

Luxoft is seeking a highly skilled engineer to advance Level 4 autonomous driving software, integrating perception, localization, fusion, behavior, and vehicle interfaces.

You will analyze complex cross-functional issues, develop feasible solutions, and lead reviews, tests, and verification across simulated and real environments. The role expects strong problem-solving and collaboration, with occasional travel for on-site validation.

Qualifications

• Deep knowledge of autonomous driving stacks including perception, localization, fusion, planning, and vehicle interfaces.
• Experience with point-cloud processing, object detection/tracking, and multi-modal fusion.
• Ability to design tests and validation across simulated and real environments.
• Strong problem-solving and cross-functional collaboration; English communication.
• Willingness to travel occasionally for on-site testing.

Responsibilities

• Analyze complex Level 4 autonomous driving issues by reviewing code, logs, and sensor data to identify problems.
• Develop evaluation options based on feasibility, risks, and system impact.
• Create prototypes to validate approaches before integration and verification.
• Provide technical direction translating objectives into actionable engineering tasks.
• Lead design and code reviews, architecture discussions, and structured troubleshooting sessions.
• Identify risks and blockers early to ensure sustainable resolution.
• Review architecture decisions for robustness and production readiness.

Skills

Autonomous driving

Perception & sensor fusion

HD mapping & SLAM

Trajectory optimization

Sensor data analysis

Point-cloud processing

Object detection & tracking

Multi-modal fusion

Transformer perception

English communication

Job description

Project description

We support our partner in developing a Level 4 autonomous driving software stack aimed at obtaining type approval. Our team is fully integrated into the partner's development organization, contributing throughout the entire development lifecycle by delivering safety-critical, high-performance software components.

Responsibilities

• - Analyze complex, cross-functional issues within the Level 4 autonomous driving stack by reviewing source code, architecture, logs, sensor data, simulation results, test evidence, and vehicle behavior to identify algorithmic, software, integration, calibration, timing, performance, hardware, interface, and data-quality problems.- Develop and evaluate solution options based on technical feasibility, risks, dependencies, implementation effort, and overall system impact, ensuring recommendations are evidence-based and clearly documented.- Create prototypes or proofs of concept as needed to validate proposed approaches before supporting their implementation, integration, and verification.- Provide technical direction by translating high-level objectives and identified issues into actionable engineering tasks.- Review architecture decisions, algorithm selections, interfaces, implementation approaches, and development outcomes for robustness, functional coverage, performance, maintainability, and production suitability.- Identify and address technical risks, dependencies, inconsistencies, knowledge gaps, and engineering blockers early to ensure sustainable resolution.- Lead design reviews, code reviews, architecture discussions, and structured troubleshooting sessions as integral components of the role.

SKILLS

Must have

• Hard skills:- Apply in-depth knowledge of autonomous driving systems, integrating perception, localization, sensor fusion, prediction, behavior and motion planning, and vehicle interfaces with hardware and software platforms.- Utilize advanced techniques such as point-cloud processing, object detection and tracking, multi-modal sensor fusion, SLAM, HD mapping, scene understanding, behavior modeling, trajectory optimization, and machine learning methods including transformer-based perception and occupancy networks.- Critically evaluate emerging physical AI technologies, considering factors like maturity, safety, integration, computational demands, and operational benefits to enhance production systems.- Engage throughout the software development lifecycle by working with existing architectures, implementing and reviewing production-grade code, and ensuring seamless integration into autonomous driving systems.- Design and contribute to test scenarios, acceptance criteria, and validation methodologies across simulated and real environments, analyzing defects and system behaviors using various testing platforms and tools.- Lead assessments of integration and release readiness, defining and reviewing KPIs related to perception accuracy, planning quality, latency, resource use, robustness, and system stability.Soft skills:- Facilitate technical collaboration by establishing a comprehensive understanding of existing systems, architectures, development environments, and constraints, while aligning objectives and solutions among diverse engineering teams.- Conduct technical workshops, design and code reviews, and troubleshooting sessions to foster shared understanding and translate decisions into actionable guidance.- Demonstrate analytical, structured, and proactive problem-solving abilities, confidently managing complex or ambiguous technical challenges toward sustainable solutions.- Communicate complex technical findings clearly and constructively challenge assumptions, supporting recommendations with objective evidence.- Exhibit a pragmatic approach combined with high technical standards, actively contributing to development, analysis, integration, troubleshooting, and validation activities.- Maintain effective communication skills in English and show readiness for periodic travel to support on-site collaboration and vehicle testing.

Nice to have

- Team player: Demonstrates the ability to work effectively within a group to achieve common goals.- Communicative: Possesses strong verbal and written communication skills for clear and efficient information exchange.- Collaborative: Skilled in partnering with others to contribute to shared success and problem-solving.