SG Technology | Lead Machine Learning Engineer

SG Technology

London

1 year ago

Applications closed

Our client, a pioneering company in autonomous vehicle technology, is seeking an accomplished Technical Lead for Embedded Automotive Software to join their onboard Software Platform team. This role demands a seasoned leader with extensive experience in developing high-performance, reliable automotive-grade software for distributed, edge computing devices. As a pivotal member of the team, the Technical Lead will design and implement software architectures to integrate machine learning-based autonomous driving (AD) solutions into an automotive L2-L3 system application. This high-impact role offers visibility across the organisation and provides technical leadership for a rapidly growing team.
The Technical Lead will drive the development and deployment of embedded software that powers advanced AI models for autonomous driving, managing complex technical programs and ensuring the resilience, compliance, and performance of embedded automotive systems. This position requires close collaboration with diverse teams and leadership in achieving key program milestones within the autonomous driving domain.
Key Responsibilities

Technical Program Leadership:Independently lead large-scale areas of embedded software development, ensuring timely delivery by effectively managing requirements, risks, development strategies, milestones, and dependencies, with a critical focus on safety and compliance.
Software Architecture Design:Design and build software architectures to integrate machine learning-based autonomous driving solutions into L2-L3 automotive systems. Ensure integration with OEM software to facilitate full sensor integration and high-quality data capture for fully autonomous applications.
Collaborative Development:Collaborate with cross-functional teams, including machine learning engineers, software developers, systems engineers, and product managers, to refine and enhance the software architecture.
Compliance and Safety: Work closely with safety and functional safety teams to ensure adherence to ISO 26262 standards and other regulatory requirements, supporting ASPICE-compliant processes.
Code Base Management:Maintain a robust, scalable code base for embedded systems to support efficient development and future scalability.
Real-Time System Management:Develop and maintain real-time Linux- and QNX-based applications for embedded automotive devices, enabling data collection, storage, and machine learning inference at the edge.
Fault Tolerance and Diagnostics:Create fault-tolerant software with comprehensive diagnostic capabilities to ensure swift issue identification and resolution in deployed automotive systems.
Mentorship and Cultural Development:Mentor engineers and lead design reviews and architecture discussions to foster a culture of technical excellence, safety, and compliance.

Essential Qualifications

Extensive experience in developing safety-critical automotive embedded software in C++ with a track record of successfully leading large technical programs and teams.
Deep understanding of ASPICE-compliant Software Development Life Cycle (SDLC) processes.
Expertise in building embedded software using the AUTOSAR architecture.
Strong leadership abilities with experience in leading cross-functional teams and engaging stakeholders across divisions.
Exceptional communication skills, capable of clearly conveying complex technical and business concepts.
Bachelors degree in Computer Science, Electrical Engineering, or a related field, or equivalent professional experience.

Desirable Qualifications

Proficiency in both C++ and Rust for embedded software development.
A Masters degree or higher in Computer Science, Electrical Engineering, or a related field.
Experience developing software for diverse automotive embedded systems and operating systems, especially Linux and QNX.
Background in L2-L3 autonomous driving applications and integrating ML-based AD solutions within automotive environments.
Familiarity with ISO 26262 functional safety standards.

This is a full-time, London-based role with a hybrid working model to foster innovation and collaboration. With core working hours, the team can determine a schedule that balances office presence and remote work. This is an exciting opportunity to lead and shape the future of autonomous driving technology in a fast-paced, innovation-driven environment.

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