설명
Work Arrangement: This role is categorized as hybrid. This means the successful candidate is expected to report to Warren three times per week, at minimum, or other frequency dictated by the business.
The Role
This role offers the opportunity to work in a collaborative team focused on using physics-based models to improve battery cell and pack design. This role will be focused on using both physical data and data output from virtual models to build coarse tools that run at the speed of design. This role will require a technical and highly motivated individual to lead workgroups of Global Virtual Engineering (GVE) engineers and design architects to develop fast synthesis tools. The role will also focus on using competitive benchmarking of both analysis methods and cell & pack designs to ensure our designs are industry leading. This individual must be motivated to understand the enterprise impact of cell & pack design decisions. The individual should have a solid understanding of battery systems, cells, and battery packs.
What You'll Do
- Accelerate cell and pack design coarse tool development by bringing technical understanding of data science and AI/ML tools
- Act as mentor and technical lead to GVE engineers developing coarse tools with data science and AI/ML
- Individually, design, develop and implement machine learning models and algorithms to improve cell and pack design
- Organize and actively ensure success of workgroups with clear deliverables and timelines for deliverables
- Organize a roadmap for tool improvement prioritizing features and enhancements
- Collaborate with design architects to prioritize feature improvements to ensure tool adoption and incorporate customer feedback
- Create and implement a tool release process with tool maintenance procedures to ensure model accuracy improvement as new data becomes available
[Additional Description]
Your Skills & Abilities (Required Qualifications)
- 3 years of experience building AI/ML models having enterprise impact
- 5+ years of experience with virtual analysis
- BS in Computer Science, Chemical, Electrical, or Mechanical Engineering Required
- Knowledge of AI/ML & data analytics methodologies, trends and technologies
- Strong organizational and leadership skills
- Strong communication and persuasion
- Solid understanding and working knowledge of fundamental physics, equations and numerical methods underpinning all software used
What Will Give You A Competitive Edge (Preferred Qualifications)
- Advanced degree (MS or greater) in Chemical Engineering, Electrochemical Engineering, Materials Engineering, Mechanical Engineering, Computer Science Engineering
- Experience in multiple CAE domains
This job may be eligible for relocation benefits
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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.