Machine Learning Engineer (Reinforcement Learning)

Join our team as a Machine Learning Engineer specializing in Reinforcement Learning. You will be responsible for building scalable systems for training and fine-tuning large generative models, implementing RL-style methods, and shipping deep learning solutions. You will also own production-oriented ML for fleet-scale assessment and design and evolve data and evaluation systems. This role requires a strong background in machine learning, deep learning, and autonomous vehicles.

• Construire des systèmes évolutifs pour l'entraînement et le réglage de modèles génératifs.
• Mettre en œuvre et itérer sur des méthodes de type RL : algorithmes, objectifs de récompense.
• Expédier des solutions d'apprentissage profond qui améliorent le triage dirigé par l'homme.
• Experience with large-scale distributed training and large-scale data processing
• Hands-on experience building and applying ML in production-grade settings, with a strong RL component (policy learning, preference/feedback optimization, or offline/online RL pipelines)
• Demonstrated impact via strong publications or a clear history of shipping impactful ML systems end-to-end
• Depth in deep learning, sequence modeling, and generative models
• Ability to lead ambiguous technical work from problem framing through reliable delivery
• M.S. or Ph.D. in Computer Science, Machine Learning, AI, or a related field—or equivalent practical experience
• Background in autonomous vehicles, robotics, or complex simulation environments
• Strong grasp of modern RL and post-training techniques in LLM, dLLM, VLA and video generations
• Python fluency and frameworks such as PyTorch
• Hands-on integration of simulation platforms with ML training and evaluation workflows
• Experience defining and operating metrics for complex, safety-critical AI systems
• Technical leadership: influencing stakeholders, aligning teams, and raising the bar for evaluation rigor
• Excellent communication—simple explanations of complex trade-offs