Embedded Software Engineer

JR Spain; Las Palmas de Gran Canaria; Presencial; EUR 50.000 - 70.000; Jornada completa

Descripción de la vacante

A leading technology firm is seeking an Embedded AI/ML Software Engineer to deploy AI/ML frameworks on automotive platforms. This remote position involves optimizing AI inference engines, interfacing with automotive-grade SoCs, and tuning performance across multiple hardware units. Candidates should have over 3 years of embedded C/C++ experience and familiarity with ML frameworks. A passion for advanced driver-assistance systems is required.

Formación

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

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 accelerators.
• Contribute to toolchains, data preprocessing, and model integration.

Conocimientos

Embedded C/C++ development

ML frameworks familiarity

Hands-on experience with QNX, RTOS, or Linux

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:

1. 3+ years in embedded C/C++ development
2. Familiarity with one or more ML frameworks: TensorFlow Lite, ONNX, TVM, etc.
3. Hands-on experience with QNX, RTOS, or Linux-based embedded platforms

Bonus:

• Knowledge of automotive safety standards (ISO 26262), or AI runtime stacks