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Internship: Embedded software engineer(m/w/x)

Gilching
Part-timeInternshipWith Home Office
AI/ML

Co-designing embedded software for space-grade SoC platforms with Model-Based Design workflows. FPGA and SoC platform experience required. Flexible schedule, study aid, career development.

Requirements

  • Strong technical foundation
  • Genuine interest in cutting-edge space technologies
  • Bachelor's or Master's in Electrical, Industrial, Computer, or Telecommunications Engineering, or related field, preferably with focus on programmable digital HW/SW systems
  • Proficiency in digital hardware design and development
  • Experience with FPGAs and SoC platforms, exposure to real-time operating systems
  • Familiarity with space-segment technologies and interest in aerospace projects or standards
  • Background in Model-Based Design, multicore architectures, heterogeneous system design with RISC-V and SPARC processors
  • Hands-on experience with adaptive embedded software, exposure to neural network projects or machine-learning workflows
  • Experience with RTEMS and TSP hypervisors for real-time and partitioned embedded systems (strong plus)
  • Understanding of fault-tolerant design principles for mission-critical aerospace applications (strong plus)
  • Knowledge of machine-learning inference techniques (DNNs, CNNs, SNNs) on embedded platforms (strong plus)
  • Familiarity with computer-vision algorithms and embedded implementation (strong plus)
  • Awareness of ECSS standards and relevance to space-segment engineering (strong plus)
  • Exposure to formal verification methods for hardware and software systems (strong plus)
  • Software design and development
  • Algorithm development
  • Fluent English (C1 or higher)

Tasks

  • Co-design and develop embedded software for space-grade SoC platforms
  • Collaborate on Model-Based Design workflows
  • Support deployments on manycore heterogeneous devices
  • Design and implement heterogeneous computing systems for aerospace
  • Explore and implement embedded machine-learning inference acceleration
  • Leverage digital and mixed analog-digital accelerator technologies
  • Engage in rapid prototyping for Software-Defined Radio applications
  • Optimize Neural Network-based applications for space use

Education

  • Bachelor's degreeOR
  • Master's degree

Languages

  • EnglishBusiness Fluent

Tools & Technologies

  • FPGAs
  • System-on-Chip (SoC)
  • Real-time operating systems
  • RISC-V
  • SPARC processors
  • RTEMS
  • TSP hypervisors
  • DNNs
  • CNNs
  • SNNs

Benefits

Flexible Working

  • Flexible schedule

Learning & Development

  • Study aid

Career Advancement

  • Career development

Snacks & Drinks

  • Free fruit
  • Free coffee

Team Events

  • Team activities
  • Sports competitions
Find the original job posting in its most current version here. Nejo automatically captured this job from the website of GMV and processed the information on Nejo with the help of AI for you. Despite careful analysis, some information may be incomplete or inaccurate. Please always verify all details in the original posting! Content and copyrights of the original posting belong to the advertising company.

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