Descrição
The Role:
Improved cellular communication standards, e.g., 5G, and infrastructure supports make rich infotainment applications in vehicles more feasible. Yet the highly dynamic cellular connectivity makes it very challenging to provide consistent Quality of Experience (QoE) to GM customers. To this end, there is an immediate demand to improved system architecture and optimization mechanisms to maintaining service quality, especially under the highly dynamic cellular networks. Data-intensive applications under cellular networks are most easily affected by network performance fluctuations due to their exclusive demands for network resources. As a result, Cloud and vehicle system co-design will offer unique opportunities in guaranteeing user QoE.
What You’ll Do:
· Understand the current status of cellar network, including deployment and communication performance.
· Algorithm design to address QoE degradation as hinted by cellular communication performance issues, including latency reduction, service continuity, service smoothness and if necessary minimum QoE sacrifice.
·Vehicle and Cloud/Edge end-to-end system design in support of the design algorithms to ensure QoE.
· Implement and test an end-to-end system in GM test vehicles, demonstrating efficacy of the system design and algorithmic contribution. Actively document and potentially further improve ideas generated while working on the system.
· Extensively evaluate system performance using a data-driven approach with good test scenario coverage.
· Practice forward-thinking, be comprehensive in system and algorithmic design, foresee research challenges and proactively identify solutions.
Required Qualifications:
- Pursuit of a Master or PhD degree
- Must be a current student
- Able to work fulltime, 40 hours per week during the summer months
- Background in mobile networks and wireless communications, particularly on Cloud/Edge computing and 4G/5G/6G standards.
- Knowledge in end-to-end system design and optimization, and protocols on handling heavy data delivery. Experience in working with data-intensive applications, e.g., video streaming.
- Experience in commonly used tools in handling video data, e.g., Gstreamer, ffmpeg, etc.
- Software engineering skills such as C++, C#, Java/Kotlin and/or Python as well as understanding of multithreading programming and real time system development. Strong in data-driven analytics
- Highly motivated to conduct quality work, independent in thinking and able to actively communicate with team members.
- Excellent communication skills in writing and verbal communication.
Preferred Qualifications:
- PhD
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).
The position is subject to export control restrictions and requires the successful candidate to be a U.S. Person (U.S. citizen, U.S. permanent resident, asylee or refugee).
Work Arrangement:
Hybrid: This role is categorized as hybrid. This means the successful candidate is expected to report to Warren, MI three times per week, at minimum [or other frequency dictated by the business].
GM will provide a one-time lump sum taxable stipend payment to eligible students selected for the 2027 Student Program - to help facilitate administration of relocation benefits, please apply using the permanent address you would move from.
Start dates for this internship role are May 24th & June 14th of 2027.
Informações sobre diversidade
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Declaração de Igualdade de Oportunidades de Emprego (EUA)
A General Motors tem orgulho de ser um empregador que oferece oportunidades iguais. Todos os candidatos qualificados serão considerados para o emprego, independentemente de raça, cor, religião, sexo, orientação sexual, identidade de gênero, origem nacional, deficiência ou status como veterano protegido.
Adaptações (EUA e Canadá)
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