Descripción

At General Motors, our product teams are redefining mobility. Through a human-centered design process, we create vehicles and experiences that are designed not just to be seen, but to be felt. We’re turning today’s impossible into tomorrow’s standard —from breakthrough hardware and battery systems to intuitive design, intelligent software, and next-generation safety and entertainment features.

Every day, our products move millions of people as we aim to make driving safer, smarter, and more connected, shaping the future of transportation on a global scale.

The Role

The successful candidate will lead development and application of Safety of the Intended Functionality methods for ADAS features (L0-L2/L2++), partnering across the engineering organization to ensure safe feature behavior from concept through validation. This work directly supports GM’s broader system safety goals for advanced vehicle technologies and requires balancing safety, availability, and feature performance across complex sensing, compute, and control architectures.

We are looking for a highly energetic and creative thinker who can apply systems-level thinking, work effectively across software, hardware, systems, and validation teams, and help strengthen GM’s approach to SOTIF for next-generation ADAS features.

What You'll Do

Lead SOTIF activities for ADAS features, including identification of triggering conditions, unknown unsafe scenarios, performance limitations, and scenario-based risk reduction strategies.
Analyze perception, fusion, planning, and controls failure modes such as false positives, false negatives, degraded sensor behavior, calibration drift, and planner instability.
Partner with ADAS feature engineers to align SOTIF work products with hazard analysis, safety concepts, safety requirements, and end-to-end traceability.
Define and support validation and verification strategies across SIL, MIL, HIL, vehicle, and scenario-based testing, including boundary conditions, regression coverage, and edge-case evaluation.
Develop clear technical recommendations that balance safety, availability, customer experience, and program timing for ADAS features.
Collaborate across perception, fusion, controls, systems, hardware, software, validation, and vehicle integration teams to deliver robust feature behavior and on-time safety content.
Support audits, assessments, reviews, and safety case activities by preparing clear technical documentation, evidence, and rationale for SOTIF-related decisions.
Contribute to continuous improvement of SOTIF methods, templates, scenario taxonomies, and best practices for ADAS and automated driving technologies.
Collaborate with R&D to develop tools for SOTIF based scenarios generation

Required Qualifications

Bachelor’s degree in Mechanical Engineering, Electrical Engineering, Aerospace Engineering, Computer Science, Systems Engineering, or a related engineering field.
5 - 7+ years of experience in systems engineering, system safety, ADAS, autonomous driving, robotics, or another safety-critical technical domain.
Strong understanding of ISO 21448 (SOTIF) and working knowledge of ISO 26262 and related safety processes.
Ability to understand complex technical systems and apply structured engineering judgment to ambiguous problems.
Strong technical leadership, communication, and collaboration skills in a cross-functional environment.
Experience defining or supporting validation plans and using data to evaluate system behavior and residual risk.

Preferred Qualifications

Advanced degree in Engineering or a related technical field.
Experience with ADAS features such as AEB, ACC, LKA, ALKS, Park Assist, or similar driver assistance functions.
Experience with object sensing technologies including camera, radar, lidar, ultrasonic sensing, and sensor fusion.
Familiarity with ADAS compute platforms, ECU/SoC architectures, AUTOSAR, QNX, POSIX RTOS, hypervisors, or safety partitioning concepts.
Hands-on experience with safety and analysis methods such as FTA, FMEA, FMEDA, STPA, or related techniques.
Experience with requirements and traceability tools such as DOORS, DNG, Jama, Medini, or similar toolchains.
Experience in scenario-based validation, edge-case mining, KPI development, and data-driven evaluation for perception-based features.
Experience supporting external audits, assessments, or safety case reviews for ADAS or automated driving systems.

GM does not provide immigration-related sponsorship for this role. Do not apply for this role if you will need GM immigration sponsorship now or in the future. This includes direct company sponsorship, entry of GM as the immigration employer of record on a government form, and any work authorization requiring a written submission or other immigration support from the company (e.g., H1-B, OPT, STEM OPT, CPT, TN, J-1, etc.)

Este puesto se clasifica como híbrido. Esto significa que se espera que el candidato seleccionado se presente en una ubicación específica al menos 3 veces por semana {o con otra frecuencia indicada por su líder}.

Este puesto podría ser elegible para beneficios de relocalización.

Información sobre diversidad

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Declaración de igualdad de oportunidades en el empleo (EE.UU.)

General Motors se enorgullece de ser un empleador que ofrece igualdad de oportunidades. Todos los solicitantes calificados serán tenidos en cuenta para el empleo sin distinción de raza, color, religión, sexo, orientación sexual, identidad de género, nacionalidad, discapacidad o condición de veterano protegido.

Adecuaciones (EE.UU. y Canadá)

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