ML Runtime Optimization Engineer

Join our team as an ML Runtime Optimization Engineer, where you'll optimize ML models and deploy them on production-grade embedded runtime environments. You'll work across the entire ML framework stack and drive performance optimization for on-road and off-road ADAS/AD stacks. This role offers a comprehensive benefits package, including health insurance, a fitness stipend, 401(k) match, learning stipend, parental leave, and on-site meals and snacks.

• Conduire l'optimisation des performances de l'apprentissage automatique sur plusieurs technologies pour les systèmes ADAS / AD.
• Développer des stratégies d'utilisation des calculs pour optimiser l'efficacité et la latence de l'inférence des modèles.
• Collaborer étroitement avec les ingénieurs ML et les développeurs de logiciels pour trouver et optimiser des solutions d'architecture de modèle efficaces.
• Experience profiling and optimizing model performance on embedded compute platforms
• Experience in working with deep learning frameworks (e.g., PyTorch, JAX, ONNX, etc.)
• 3+ years of experience with ML accelerators, GPU, CPU, SoC architecture and micro-architecture
• Bachelors in Electrical Engineering or Computer Science, OR . in Computer Science, Mathematics, Physics or a related field
• Strong software development skills with the focus on embedded programming
• Built an ML optimization framework from scratch before
• Deployed ML solutions to embedded chips for real time robotics applications
• Don’t meet every single requirement? If you’re excited about this role but your past experience doesn’t align perfectly with every qualification in the job description, we encourage you to apply anyway. You may be just the right candidate for this or other roles
• or PhD in a ML related area