Embedded Software Engineer

JR Spain; Alicante; Presencial; EUR 30.000 - 50.000; Jornada completa

Descripción de la vacante

A renowned technology company is looking for an Embedded AI/ML Software Engineer to work on automotive platforms. You will deploy and optimize AI inference engines and interface with sensor modules. Candidates should have over three years of C/C++ development experience and familiarity with ML frameworks. This position is fully remote, offering a flexible hybrid model.

Formación

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

Responsabilidades

• Deploy and optimize AI inference engines on embedded targets.
• Interface with sensor and perception modules on automotive SoCs.
• Tune performance across CPU, DSP, GPU, and neural accelerators.
• Contribute to toolchains, data preprocessing, and model integration.

Conocimientos

Embedded C/C++ development

Machine Learning frameworks

Real-time systems

Performance tuning

Herramientas

QNX

RTOS

Linux

TensorFlow Lite

ONNX

Descripción del empleo

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:

1. Deploy and optimize AI inference engines (e.g., ONNX, TFLite) for embedded targets
2. Interface with sensor and perception modules on automotive-grade SoCs
3. Tune performance across CPU, DSP, GPU, and neural accelerator units
4. Contribute to toolchains, data preprocessing, and model integration workflows

Requirements:

• 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