Senior AI Engineer – Automotive In-Cabin Monitoring

Senior AI Engineer – Automotive In-Cabin Monitoring
About the Role
We are looking for a highly motivated Senior AI Engineer to join our Automotive AI team and contribute to the development of next-generation In-Cabin Monitoring Systems. You will design, develop, optimize, and deploy state-of-the-art computer vision and deep learning solutions for safety, comfort, and personalization features in future vehicles.
The ideal candidate combines strong machine learning expertise with hands-on automotive experience and a proven track record of deploying AI models on embedded automotive platforms.

Key Responsibilities
AI & Computer Vision Development

• Design and develop advanced computer vision algorithms for automotive in-cabin applications
• Develop and maintain deep learning models using CNNs, Transformers, Vision Transformers (ViT), and multimodal architectures.
• Experience with SLAM is considered an asset
• Build data pipelines for dataset preparation, annotation, validation, and continuous improvement.
• Develop training and evaluation methodologies using real-world and synthetic datasets.

Embedded AI Deployment & Optimization

• Optimize AI models for embedded automotive SoCs and edge computing platforms.
• Perform model compression, quantization, pruning, and knowledge distillation.
• Maximize inference performance and model memory footprint
• Deploy models using popular embedded NPU frameworks from different SoCs.

Product Development

• Collaborate with system architects, software engineers, product lead, business developers and sensor experts to integrate AI solutions into production platforms.
• Support the complete development lifecycle from prototyping through series production.
• Participate in customer technical discussions and requirement analysis.
• Support safety, validation, and compliance activities for automotive AI products.

Research & Innovation

• Evaluate emerging AI technologies and state-of-the-art computer vision methods.
• Contribute to innovation activities, patents, publications, and technical roadmaps.
• Investigate synthetic data generation and self-supervised learning approaches for automotive perception.

Required Qualifications

• Master’s degree or PhD in:
  • Computer Science
  • Artificial Intelligence
  • Electrical Engineering
  • Robotics
  • Applied Mathematics
  • Related field
• 5+ years of professional experience in AI/ML development, preferably in Automotive context.
• Strong background in:
  • Computer Vision
  • Deep Learnin
  • Image Processing
  • Pattern Recognition
  • SLAM

• Expert knowledge of:
  • Python
  • PyTorch
  • TensorFlow or equivalent frameworks
  • OpenCV
• Strong understanding of:
  • Object Detection
  • Semantic/Instance Segmentation
  • Pose Estimation
  • Human Activity Recognition
  • Face and Eye Tracking
  • 3D Vision and Depth Estimation

• Experience developing AI solutions from concept to deployment.

Automotive Experience (Mandatory)
Candidates must demonstrate experience working with one or more of the following:

• Automotive OEMs / Tier-1 suppliers / Tier-2 suppliers
• Automotive semiconductor or sensing companies

Experience should include:

• Automotive perception systems
• ADAS and/or In-Cabin Monitoring
• Camera-based sensing systems
• Functional safety aware AI development
• Automotive software development lifecycle
• Customer-facing engineering activities

Experience with production programs supporting vehicle launches is highly desirable.

Embedded AI & SoC Experience (Nice to have)
Proven experience optimizing and deploying machine learning models on embedded platforms such as:

• Qualcomm Snapdragon Ride
• NVIDIA DRIVE
• Texas Instruments Jacinto
• Renesas R-Car
• NXP Platforms
• Ambarella
• ARM-based AI accelerators

Demonstrated expertise in:

• Quantization-aware training
• INT8 optimization
• Model pruning
• Neural architecture optimization
• Runtime profiling
• Latency and throughput optimization
• Edge AI deployment

Preferred Qualifications

• Experience with RGB, NIR, IR, ToF, or depth sensing technologies.
• Knowledge of synthetic data generation and simulation environments.
• Familiarity with automotive standards:
  • ISO 26262
  • ISO/PAS 8800
  • ASPICE
  • SOTIF (ISO 21448)

• Experience with CI/CD and MLOps pipelines.
• C++ development for production embedded systems.
• Experience leading technical work packages or mentoring junior engineers.

Ideal Candidate Profile
A successful candidate is a hands-on AI engineer with deep computer vision expertise, proven experience in the automotive industry, and a strong track record of optimizing and deploying AI models on resource-constrained automotive SoCs. They are comfortable working across research, engineering, and customer-facing activities to bring production-ready in-cabin monitoring solutions to market.