Develops real-time Linux platforms for AI robotics, integrating controls, ML algorithms, and drivers on multicore ARM systems. Requires MS degree, production Linux RT experience, C/C++ proficiency, and ROS 2 expertise.
Salary not listed
On-siteEmbedded Engineering
About the role
Responsibilities
Design, adapt, and integrate POSIX-compliant systems for advanced robotics and machine learning (ML) applications.
Develop the framework for integration of controls, machine learning and supporting algorithms with real-time tasks.
Collaborate with Controls and Machine Learning engineers to develop and optimize high performance autonomous systems.
Develop and maintain drivers for integration with real-time robotic middleware.
Build tools to monitor, verify and optimize system performance, ensuring reliable and deterministic behavior.
Contribute to a deterministic and reproducible build and test environment for efficient development.
Work with functional safety engineers to support standards compliance, audit readiness, and traceability.
Develop robust solutions for over-the-air (OTA) updates, calibration management and software deployment strategies.
Tackle complex, real-world challenges alongside a multidisciplinary team of experts.
Qualifications
Must-have
MS in computer engineering, computer science or a related discipline.
Production experience with bringup and configuration of Linux PREEMPT_RT and similar operating systems (e.g. QNX).
Strong understanding of Linux device trees, scheduling and memory management.
Experience with multicore ARM SoCs, interprocess/intercore communications and message passing.
Proficiency in C and C++
Experience with ROS 2 middleware and alternatives (e.g. FastDDS, CycloneDDS, Zenoh).
Familiarity with container technologies (Docker, Containerd, Overlayfs).
Understanding of toolchains (compilers, linkers, debuggers, static analysis tools)
Nice-to-have
Familiarity with communication protocols (e.g. Ethernet, EtherCAT, CAN, CANOpen).
Knowledge of ARM SIMD/NEON architecture extensions.
Proficiency in additional programming languages (e.g. Python, Rust, Golang).
Expertise with multi-language build systems (e.g. Bazel).
Experience with Hypervisors (e.g. QNX Hypervisor, Jailhouse, Xen).
Understanding of container orchestration (Kubernetes).
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