설명
Hybrid: This role is categorized as hybrid. This means the successful candidate is expected to report to Austin TX IT Innovation Center or Warren Michigan 3 days per week (T-W-Th)
Who We Are
We are an engineering-focused IT organization responsible for the platforms, tools, and data ecosystems that power GM’s virtual engineering and simulation (CAE) capabilities. Our teams design , build, and operate high-performance computing, data, and AI/ML integration solutions that enable engineers to explore more design options, accelerate development cycles, and improve product quality. We partner closely with CAE, software, data science, and infrastructure teams to turn cutting-edge technologies into robust, production-ready capabilities that make GM’s vehicles safer, more efficient, and more innovative.
The Role
We are seeking a Senior Systems Engineer to lead the implementation, integration, and operationalization of AI/Machine Learning (AIML) solutions for the CAE engineering community. In this role, you will implement AIML based POC's as well as turn those POC's into robust, supportable capabilities by installing, configuring, and integrating commercial and custom AIML tools with GM’s CAE applications, HPC environments, and data platforms. You will partner closely with CAE engineers, other systems engineers, and infrastructure teams to ensure these solutions are reliable, performant, and straightforward for engineering users to adopt at scale.
What You’ll Do
-
Lead the installation, configuration, and integration of AIML software and services into existing and new CAE workflows, including on-prem and cloud/HPC environments.
-
Integrate CAE tools, data sources, and AIML components (e.g., APIs, agents, pipelines, UIs) with enterprise platforms such as HPC clusters, Azure, data lakes, and Simulation Process and Data Management solutions.
-
Define and maintain system-level requirements, interfaces, and architecture diagrams for AIML-enabled CAE solutions, ensuring traceability and alignment with enterprise standards.
-
Develop and execute installation, integration, and regression test plans to validate end-to-end CAE workflows, including performance, reliability, and security checks.
-
Partner with CAE engineers and business stakeholders to harden and scale successful AIML POCs, including packaging, deployment, monitoring, and support hand-off.
-
Establish and improve operational processes (versioning, configuration management, logging, observability, incident response) for AIML-enabled CAE applications.
-
Ensure all solutions comply with GM security, data governance, and responsible AI guidelines, including appropriate handling of engineering and proprietary data.
-
Create and maintain user guides, runbooks, and integration documentation to support CAE engineers, support teams, and partner IT organizations.
-
Provide technical leadership and mentorship to peers and junior engineers on CAE integration patterns, AIML solution deployment, and systems engineering best practices.
-
Stay current on emerging AIML and CAE software capabilities and recommend pragmatic opportunities to simplify workflows, improve throughput, and reduce cycle time for engineering teams.
Your Skills & Abilities (Required Qualifications)
-
Bachelor’s degree in Systems Engineering, Software Engineering, Computer Science, Mechanical/Automotive Engineering, or a related technical field.
-
7+ years of experience in systems engineering and/or software integration roles, with a focus on complex, distributed or HPC-based systems.
-
Hands-on experience installing, configuring, and integrating engineering or scientific software (e.g., CAE solvers, pre/post tools, optimization/MBSE/AI tools) across desktop, HPC, and/or cloud environments.
-
Strong background in systems engineering practices (requirements, interfaces, architecture, validation, and lifecycle management).
-
Practical understanding of AI/ML concepts and patterns (e.g., model endpoints, inference services, pipelines, RAG/agentic workflows) and how they integrate into applications and workflows.
-
Proficiency with scripting and automation (e.g., Python, shell, CI/CD tools) for installation, configuration, and validation of integrated systems.
-
Experience working with HPC or cloud-based compute environments (e.g., job schedulers, containers, GPU resources, monitoring and logging tools).
-
Demonstrated ability to collaborate with cross-functional teams (CAE engineers, software developers, data scientists, infrastructure, cybersecurity) to deliver integrated solutions.
-
Excellent communication, documentation, and stakeholder-management skills; able to explain complex technical topics to diverse audiences.
What Will Give You a Competitive Edge (Preferred Qualifications)
-
Master’s degree in Engineering, Systems Engineering, Computer Science, or a related field.
-
Direct experience with CAE tools and workflows (e.g., structural, CFD, optimization, SPDM/EPDM) and how engineering teams run simulations in practice.
-
Experience integrating or deploying commercial AIML/physics-AI tools within engineering environments.
-
Familiarity with GM-like enterprise environments (regulated, safety-critical, or automotive) and associated security and compliance expectations.
#LI-CK1
Gm does not provide immigration-related sponsorship for this role. Do not apply for this role if you will need gm immigration sponsorship (e.g., H-1B, TN, STEM, OPT, etc.) Now or in the future.
This job may be eligible for relocation benefits.
다양성 정보
General Motors는 법적으로 금지된 차별을 배제하는 것은 물론 포용성과 소속감을 진정으로 장려하는 직장이 되기 위해 노력하고 있습니다. 당사는 다양성이 보장되는 환경에서 직원들이 역량을 발휘하고 우리 고객을 위한 더 좋은 제품을 개발할 수 있다고 믿습니다. 따라서 입사에 관심 있는 사람이 있다면 포지션별 주요 업무와 자격을 확인하고 본인이 보유한 기술과 능력에 부합하는 모든 포지션에 적극적으로 지원하기를 장려합니다. 지원자는 채용 과정에서 역할 관련 평가(해당하는 경우) 및/또는 채용 전 스크리닝을 통과해야 합니다. 자세한 정보는 GM 채용 과정 안내를 참고하십시오.
공평한 취업 기회 선언 (미국)
General Motors는 공평한 기회를 제공하는 고용주임을 자부합니다. 자격을 만족하는 지원자는 인종과 피부색, 성별, 성적 지향, 성별 정체성, 국적, 장애, 재향 군인 보호법 적용 여부와 상관없이 채용 후보로서 심사를 받습니다.
숙소 (미국 및 캐나다)
General Motors는 장애인을 포함한 모든 구직자들에게 취업 기회를 제공합니다. 구직이나 취업 지원에 도움이 되는 합리적인 숙소가 필요한 경우 [email protected]으로 이메일을 보내시거나 800-865-7580으로 전화주십시오. 이메일에, 귀하가 요청하는 특정한 숙소에 대한 설명과 귀하가 지원하는 직무와 채용 요청서 번호를 포함해주세요.
