Expert - Embedded AI Operating System Architect

A leading advanced technology research organization focused on intelligent energy, industrial automation, and next-generation embedded systems is seeking a Senior Expert - Embedded AI Operating System Architect.

This role will drive the architecture of embedded real-time operating systems and middleware platforms that combine deterministic real-time behavior with modern AI capabilities. The position sits at the intersection of operating systems, embedded computing, AI inference, heterogeneous hardware acceleration, and functional safety.

The successful candidate will lead the development of foundational software technologies supporting intelligent edge devices in industrial, energy, and automotive environments.

Key Responsibilities

Embedded AI Operating System Architecture

• Define next-generation embedded operating system architectures that combine:

• Real-time determinism
• AI inference capabilities
• Heterogeneous compute acceleration

• Design middleware and runtime frameworks enabling efficient deployment of AI workloads on resource-constrained devices.
• Develop scalable software architectures supporting intelligent autonomous functions.

Real-Time Performance & Determinism

• Optimize operating system behavior for:

• Low-latency execution
• Predictable response times
• High reliability

• Design scheduling mechanisms that support both traditional real-time tasks and AI workloads.
• Develop techniques to minimize jitter and end-to-end latency.

Hardware & System Optimization

• Perform low-level performance analysis and optimization across:

• CPUs
• GPUs
• NPUs
• Memory subsystems
• Communication interfaces

• Analyze hardware bottlenecks and improve utilization of heterogeneous computing resources.
• Develop strategies to reduce contention across shared resources.

AI Runtime & Resource Management

• Architect efficient frameworks for:

• Embedded AI inference
• Resource orchestration
• Heterogeneous workload scheduling

• Enable deterministic execution of machine learning models on embedded platforms.
• Improve runtime efficiency and scalability for edge AI applications.

System Reliability & Safety

• Enhance operating system robustness and fault tolerance.
• Support development of software platforms suitable for safety-critical environments.
• Contribute to system-level strategies for reliability and functional safety.

• Master's degree in:

• Computer Science
• Computer Engineering
• Electrical/Electronic Engineering
• Related discipline

• PhD is highly desirable.

Operating Systems Expertise

• Deep knowledge of:

• Linux kernel architecture
• Real-time operating systems (RTOS)
• POSIX-compliant systems

• Extensive experience with:

• Kernel scheduling
• Real-time scheduling algorithms
• Memory management
• Process isolation
• Interrupt handling

Embedded Systems Knowledge

• Strong understanding of embedded hardware architectures, including:

• SoCs
• MPUs
• MMUs
• Interrupt controllers
• Cache hierarchies
• Memory virtualization

• Experience with ARM and/or RISC-V platforms.
• Knowledge of hardware resource contention mitigation techniques.

Programming Skills

• Expert-level C and C++ programming.
• Experience with:

• Assembly language development
• Device driver implementation
• Low-level system software development

AI & Edge Computing

• Experience with embedded AI frameworks such as:

• TensorFlow Lite
• LiteRT
• Similar edge inference frameworks

• Understanding of deterministic AI inference mechanisms.
• Knowledge of machine learning techniques including:

• CNNs
• DNNs
• SVMs

Distributed & Middleware Systems

• Expertise in distributed and service-oriented architectures.
• Experience designing systems that improve:

• Determinism
• Reliability
• End-to-end latency

Preferred Qualifications

Automotive & Industrial Systems

• Knowledge of:

• OSEK/VDX
• AUTOSAR Classic
• Automotive software architectures

Functional Safety

• Familiarity with:

• ISO 26262
• IEC 61508
• Safety-critical software development processes

Performance Engineering

• Strong background in:

• Embedded system profiling
• Performance optimization
• Latency analysis
• Resource scheduling

Leadership & Soft Skills

• Strong architectural thinking and systems-level problem-solving capabilities.
• Excellent communication and collaboration skills.
• Ability to work effectively in multidisciplinary international teams.
• Self-driven with strong initiative and ownership.
• Fluent English communication skills.