Embedded Software Engineer

JR Spain; Marbella; Presencial; EUR 45.000 - 70.000; Jornada completa

Descripción de la vacante

A technology company in the automotive sector is seeking an Embedded AI/ML Software Engineer. The role involves deploying AI/ML frameworks on automotive platforms and offers remote work options in Spain or Egypt. Candidates should have over 3 years in embedded C/C++ development and familiarity with ML frameworks. Optimizing real-time systems will be key, and knowledge of automotive safety standards is a plus.

Formación

• 3+ years of experience in embedded C/C++ development.
• Hands-on experience with QNX, RTOS, or Linux-based embedded platforms.
• Familiarity with AI/ML frameworks like TensorFlow Lite, ONNX.

Responsabilidades

• Deploy and optimize AI inference engines for embedded targets.
• Interface with sensor and perception modules on automotive-grade SoCs.
• Tune performance across CPU, DSP, GPU, and neural accelerator units.

Conocimientos

Embedded C/C++ development

AI inference engines optimization

Familiarity with ML frameworks

Performance tuning across CPUs, DSPs

Herramientas

QNX

RTOS

Linux-based platforms

Descripción del empleo

Social network you want to login/join with:

Embedded AI/ML Software Engineer – Automotive Platforms (Spain / Egypt)

Work Location: Remote (Spain or Egypt) | Hybrid optional

Employment Type: Full-time Contractor via TechTeamz

Project Area: Advanced driver-assistance systems (ADAS), in-vehicle AI compute

We’re hiring Embedded Engineers with a passion for deploying AI/ML frameworks on automotive platforms. Join a fast-paced, forward-looking team developing real-time systems at the edge.

Responsibilities:

• Deploy and optimize AI inference engines (e.g., ONNX, TFLite) for embedded targets
• Interface with sensor and perception modules on automotive-grade SoCs
• Tune performance across CPU, DSP, GPU, and neural accelerator units
• Contribute to toolchains, data preprocessing, and model integration workflows
• 3+ years in embedded C/C++ development
• Familiarity with one or more ML frameworks: TensorFlow Lite, ONNX, TVM, etc.
• Hands-on experience with QNX, RTOS, or Linux-based embedded platforms
• Bonus: knowledge of automotive safety standards (ISO 26262), or AI runtime stacks