Centralized compute (HPC / Brain platforms) * Function allocation across edge and central layers ... Standardized interfaces and abstraction layers * Ensure traceability: * System → Software → ...
Centralized compute (HPC / Brain platforms) * Function allocation across edge and central layers ... Standardized interfaces and abstraction layers * Ensure traceability: * System → Software → ...
Brain Computer Interface information
See Michigan salary details
$10.06 - $15.31
2% of jobs
$15.31 - $20.57
0% of jobs
$20.57 - $25.83
0% of jobs
$25.83 - $31.08
3% of jobs
$31.08 - $36.34
5% of jobs
$36.34 - $41.60
14% of jobs
$41.74 is the 25th percentile. Wages below this are outliers.
$41.60 - $46.86
28% of jobs
$46.86 - $52.11
18% of jobs
$53.83 is the 75th percentile. Wages above this are outliers.
$52.11 - $57.37
14% of jobs
$57.37 - $62.63
11% of jobs
$62.63 - $67.88
5% of jobs
$10
$47
$67
How much do brain computer interface jobs pay per hour?
As of Jul 28, 2026, the average hourly pay for brain computer interface in Michigan is $47.88, according to ZipRecruiter salary data. Most workers in this role earn between $41.92 and $54.47 per hour, depending on experience, location, and employer.
What is a Brain Computer Interface job?
A Brain-Computer Interface (BCI) job involves developing systems that enable direct communication between the brain and external devices. Professionals in this field work on hardware and software to interpret neural signals, often for medical, assistive, or neurotechnology applications. Roles can include research, software engineering, signal processing, and machine learning to improve BCIs' accuracy and functionality. These jobs are common in healthcare, neuroscience, gaming, and AI-driven human augmentation industries.
What are some common challenges faced by professionals working in Brain Computer Interface roles?
Professionals in Brain Computer Interface roles often face challenges related to accurately interpreting complex neural signals, minimizing noise in data, and ensuring that BCI systems are intuitive for end-users. They frequently collaborate with neuroscientists, engineers, software developers, and clinicians to overcome technical and usability barriers. Balancing research innovation with real-world applicability can be demanding, and staying current with rapidly advancing technology is essential. These challenges make the field dynamic and rewarding for those passionate about shaping the future of human-computer interaction.
What are the key skills and qualifications needed to thrive in the Brain Computer Interface position, and why are they important?
To thrive in a Brain Computer Interface role, you typically need a strong background in neuroscience, biomedical engineering, or computer science, coupled with experience in signal processing and neural data analysis. Familiarity with tools such as MATLAB, Python, EEG/MEG systems, and relevant certifications in neurotechnology are highly valuable. Strong problem-solving abilities, collaboration, and effective communication skills are essential for working on multidisciplinary teams and translating research into practical applications. These skills ensure that you can design, develop, and refine advanced BCI systems that meet both technical and user needs in this rapidly evolving field.
What are the most commonly searched types of Brain Computer Interface jobs in Michigan? The most popular types of Brain Computer Interface jobs in Michigan are:
What are popular job titles related to Brain Computer Interface jobs in Michigan? For Brain Computer Interface jobs in Michigan, the most frequently searched job titles are:
What job categories do people searching Brain Computer Interface jobs in Michigan look for? The top searched job categories for Brain Computer Interface jobs in Michigan are:
Full-time
Posted 2 days ago
Stellantis rating
7.5
Based on 130 frontline employees who took The Breakroom Quiz
15th of 44 rated automakers
Job description
As a Senior Technical Fellow for Edge Optimization Architecture, you will define and drive the transformation from traditional distributed ECU architectures to a software-defined, centralized compute model with optimized edge nodes (Zero-Edge / Zonal Architecture).
You will shape the end-to-end architectural strategy for edge systems, ensuring optimal balance between centralized HPC compute and distributed edge functions, maximizing performance, scalability, cost efficiency, and reuse across vehicle programs.
This role requires deep expertise in E/E architecture, embedded software, networking, and system optimization, combined with strong leadership to influence enterprise-wide transformation and guide engineering teams through next-generation architecture adoption.
Key Responsibilities
1 - Architectural Leadership (Edge Optimization Strategy)
2- System Optimization & Functional Allocation
3- Innovation & Technology Leadership
4- Technical Expertise (End-to-End E/E + SW Stack)
4- Cross-Domain Integration & Collaboration
5- Performance Optimization & Continuous Monitoring
6- Mentorship & Technical Leadership
7- Governance & Operational Support
8- Documentation & Standards
9- Stakeholder Engagement & Executive Influence
10 - External Representation
11- Knowledge Sharing & Capability Building
Qualifications
2- Experience
3- Technical Skills
4- Leadership
5- Problem-Solving
6- Innovation
You will shape the end-to-end architectural strategy for edge systems, ensuring optimal balance between centralized HPC compute and distributed edge functions, maximizing performance, scalability, cost efficiency, and reuse across vehicle programs.
This role requires deep expertise in E/E architecture, embedded software, networking, and system optimization, combined with strong leadership to influence enterprise-wide transformation and guide engineering teams through next-generation architecture adoption.
Key Responsibilities
1 - Architectural Leadership (Edge Optimization Strategy)
- Define and drive the Edge Optimization Architecture vision, including:
- Zonal architecture (I/O aggregators, domain/zonal ECUs)
- Centralized compute (HPC / Brain platforms)
- Function allocation across edge and central layers
- Establish architectural principles for:
- Minimizing edge complexity
- Maximizing software centralization and reuse
- Enabling scalable software-defined vehicle platforms
2- System Optimization & Functional Allocation
- Lead system-level optimization strategies across:
- CPU, memory, network bandwidth, and latency
- Function placement (edge vs HPC)
- Define and enforce function allocation rules and trade-offs:
- Safety-critical vs centralized execution
- Latency-sensitive vs cloud/offload capable workloads
- Drive resource budgeting and KPI-based architecture validation
3- Innovation & Technology Leadership
- Lead innovation in:
- Zero-Edge / reduced ECU architectures
- Ethernet-based vehicle networking
- Service-Oriented Architectures (SOA) and middleware
- AI-driven system optimization and resource prediction
- Evaluate and guide adoption of emerging technologies:
- HPC platforms, virtualization, containerization
- Edge abstraction layers and adaptive middleware
4- Technical Expertise (End-to-End E/E + SW Stack)
- Provide deep expertise in:
- E/E system architecture (vehicle-level)
- Embedded software architecture (AUTOSAR Classic/Adaptive, POSIX, RTOS)
- High-speed automotive networking (CAN, LIN, Ethernet)
- Distributed vs centralized compute models
- Lead technical decisions on:
- Zonal controller design
- Sensor/actuator integration models
- Data flow and service communication patterns
4- Cross-Domain Integration & Collaboration
- Collaborate across domains:
- ADAS, Body, Infotainment, Connectivity, Powertrain
- Drive consistent architecture across:
- Hardware, system, and software organizations
- Ensure alignment between:
- Functional architecture
- Network architecture
- Software platform strategy
5- Performance Optimization & Continuous Monitoring
- Define and govern architecture KPIs:
- CPU load, memory footprint, network utilization
- Latency, determinism, and scalability metrics
- Drive continuous monitoring and predictive optimization frameworks
- Lead root cause analysis and resolution of system bottlenecks
6- Mentorship & Technical Leadership
- Mentor senior architects and engineering leaders across domains
- Build organizational capability in:
- Edge optimization principles
- Software-defined architecture
- Foster a culture of:
- Engineering excellence
- Data-driven decision making
- Continuous improvement
7- Governance & Operational Support
- Actively support program execution:
- Critical issue resolution
- Technical trade-offs and arbitration
- Milestone and architecture readiness reviews
- Define and enforce:
- Architectural guidelines
- Design rules and best practices
8- Documentation & Standards
- Establish and maintain:
- Reference architectures for edge optimization
- Design guidelines for zonal and centralized architectures
- Standardized interfaces and abstraction layers
- Ensure traceability:
- System → Software → Deployment architecture
9- Stakeholder Engagement & Executive Influence
- Engage executive leadership on:
- Architecture strategy
- Trade-offs and investment decisions
- Provide clear, data-driven insights on:
- Cost vs performance vs complexity trade-offs
- Influence enterprise-wide transformation initiatives
10 - External Representation
- Represent the organization in:
- Industry consortiums (SDV, AUTOSAR, Ethernet standards)
- Technology forums and conferences
11- Knowledge Sharing & Capability Building
- Identify training needs and lead:
- Architecture upskilling programs
- Cross-domain knowledge sharing initiatives
- Promote reuse of best practices across global teams
Qualifications
- Education
- Master's degree in Computer Science, Electrical Engineering, or related field
- PhD preferred (Systems Architecture, Distributed Systems, or Automotive E/E)
2- Experience
- 15+ years in automotive software and system development
- 10+ years in:
- E/E architecture
- Software architecture
- System-level design and optimization
- Proven experience in:
- SDV transformation, HPC-based architectures, or zonal architectures
3- Technical Skills
- Expert knowledge of:
- Automotive software standards (AUTOSAR Classic & Adaptive)
- Embedded systems (C/C++, RTOS, POSIX systems)
- Strong expertise in:
- Vehicle networks (CAN, LIN, Ethernet, TSN)
- Distributed and centralized compute architectures
- Middleware and service-oriented communication
- Strong understanding of:
- Memory management, multi-core systems, and real-time constraints
- Virtualization and abstraction layers
- Functional safety (ISO 26262) and system robustness
4- Leadership
- Demonstrated ability to:
- Lead enterprise-level architecture transformations
- Influence senior leadership and cross-functional teams
- Strong communication and executive presentation skills
5- Problem-Solving
- Exceptional ability to:
- Solve complex cross-domain system challenges
- Navigate trade-offs under constraints (cost, safety, performance)
6- Innovation
- Proven track record of:
- Driving architectural innovation
- Influencing industry direction in SDV / E/E evolution
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