2025 ML Engineer Embedded

Simi Reality Motion Systems; Unterschleißheim; Hybrid; EUR 55.000 - 75.000; Vollzeit

Zusammenfassung

A leading company in software development seeks a motivated ML Engineer Embedded to enhance vehicle interior monitoring solutions. You will collaborate with an AI team, ensuring deep learning models operate efficiently on embedded systems. The position offers flexible hours and the chance to work remotely part-time, providing a fulfilling opportunity in a supportive environment.

Leistungen

Flexible hours

Modern office

Qualifikationen

• Experience with NN model optimization techniques for embedded hardware (quantization, pruning).
• Experience with training deep neural networks and their evaluation.
• Practical experience in machine learning projects.

Aufgaben

• Porting and integrating vision-based deep learning models to low-power embedded devices.
• Work with ML team on model optimization methods (pruning, quantization, etc.).
• Test the feasibility of deploying models on SoC.

Kenntnisse

Model optimization techniques

Deep learning

Programming in Python

C++

Unix-based operating systems (Linux)

Ausbildung

Master's degree in computer science or similar

Tools

ONNX

TF Lite

PyTorch

numpy

Jobbeschreibung

Join to apply for the ML Engineer Embedded role at Simi Reality Motion Systems.

We are seeking a highly motivated and skilled ML Engineer Embedded to join our AI team. As an ML Engineer Embedded, you will ensure that our ML solutions for vehicle interior monitoring work on SoCs in automotive environments. You will collaborate with software developers and other ML engineers to make our ML algorithms ready for production.

Key Responsibilities:

• Porting and integrating vision-based deep learning models to low-power embedded devices.
• Work with ML team on model optimization methods (pruning, quantization, distillation, etc.).
• Performance profiling (inference speed, quantitative metrics) after model optimizations.
• Test the feasibility of deploying state-of-the-art deep learning models on SoC.
• Document the model-hardware compatibility matrix.
• Testing the deployability of ML models using the SoC's PC simulator (if available).
• Adapt the perception pipeline (pre- and post-processing) for the SoCs.
• Provide assistance and feedback to the ML team for training deep neural networks.
• Implement well-structured and documented code for porting, testing, and performance evaluations.

Requirements:

• Master's degree in computer science or similar (Please send your detailed diploma).
• Experience and knowledge with NN model optimization techniques for embedded hardware, e.g., quantization, pruning, etc.
• Experience with NN model porting to embedded systems.
• Experience with training deep neural networks and their evaluation.
• Practical hands-on experience in machine learning projects.
• Good programming skills in Python, including packages like ONNX, TF Lite, PyTorch, numpy, etc.
• Familiarity with C++.
• Experience with Unix-based operating systems (Linux etc.).
• Fluent English.

Good to have:

• Experience with parallelising ML models in SoCs.
• German B2 level appreciated.

We offer responsibility, flat hierarchies, flexible hours, and the possibility to work from our modern office in Unterschleißheim or remotely part of the time. Join our motivated team dedicated to making driving safer!

Details:

• Seniority level: Associate
• Employment type: Full-time
• Job function: Information Technology
• Industry: Software Development