Company Description

CS Group Canada, a subsidiary of CS Group (part of the Sopra Steria Group), is a leader in the development and certification of safety-critical systems in the aerospace, electric, and autonomous driving industries.

Joining CS Group Canada means taking part in complex, high-tech projects for some of the most prestigious system manufacturers in North America, while benefiting from competitive salaries, comprehensive benefits, and flexible work arrangements.

Job Description

As a Safety Expert for Machine Learning, you will address one of the most challenging questions in the field: ensuring the safety and reliability of non-deterministic, ML-based ADAS components.

Your responsibilities will include:

• Researching, defining, and pioneering best practices and standards for the verification and validation of ML systems, where traditional safety methods may not apply,

• Applying STPA (System-Theoretic Process Analysis) and related system-safety techniques to identify unsafe control actions and derive ML-specific safety requirements,

• Collaborating closely with World Understanding and Behavior teams to define processes for data quality, model robustness, and Operational Design Domain (ODD),

• Developing and formalizing novel safety arguments and evidence to support production-ready deployment of AI-based ADAS features,

• Acting as a thought leader, helping shape the integration of machine learning into safety-critical automotive systems.

Qualifications

• Bachelor’s or Master’s degree in Computer Science, Electrical/Computer Engineering, AI/ML Engineering, or a related discipline,

• Strong expertise in functional safety and AI/ML safety challenges, ideally in the context of automotive ADAS and autonomous systems,

• Advanced studies (PhD) in AI safety, ML validation, or related research areas are considered a strong asset.

• Solid understanding of machine learning model development, validation, and testing, and life-cycle data management,

• Practical experience applying STPA, FMEA, or similar system-theoretic hazard analyses to automotive or aerospace systems.

• Knowledge of emerging standards and guidelines for ML safety (e.g., ISO 21448 – SOTIF, ISO 8800, UL 4600),

• Ability to bridge the gap between research and practical engineering implementation,

• Collaborative mindset, able to work across data, perception, and system safety teams.

Additional Information

Please note that only selected candidates and Permanent Residents/Canadian Citizens will be contacted.

Job Types: Full-time, Permanent

CS Group Canada values diversity in the workplace and encourages women, visible minorities, ethnic minorities, aboriginal people, and people with disabilities to apply.

Benefits:

• Hybrid Work
• Industry leading medical, dental, and vision Insurance
• Access to a telemedicine service
• RRSP program
• Personal and sick days
• Recreation room with pool table and foosball table

All your information will be kept confidential according to EEO guidelines.