VLA/WAM Research Engineer

Flexion is building foundation models for humanoid robots. The VLA/WAM Research Engineer will develop model architectures, train and adapt models across robot embodiments, and improve capabilities using simulated and real-world robot experience.

Responsibilities:

• VLA/WAM Architecture: Design and develop multimodal foundation models combining vision, language, robot state, actions, and temporal context for general-purpose robotic control
• Foundation Model Pretraining: Develop and execute large-scale pretraining across diverse robot embodiments, teleoperation, egocentric human data, and simulated experience
• Training Recipes & Scaling: Improve data mixtures, training objectives, optimization strategies, and distributed training workflows to deliver increasingly capable foundation models on a regular cadence
• World-Action Models: Develop predictive world and action models for representation learning, future-state prediction, planning, and robot policy improvement
• Adaptation & Mid-training: Develop methods to efficiently adapt pretrained models to new tasks, environments, embodiments, and capabilities
• Post-training & Reinforcement Learning: Improve models using real-world and simulated robot experience, including imitation learning, RL, reward/value-guided learning, and specialist-to-generalist distillation
• Continual Learning: Develop methods to learn from autonomous rollouts, failures, interventions, and recoveries while retaining existing capabilities and avoiding catastrophic forgetting
• Evaluation & Research: Design rigorous experiments, evaluate models in simulation and on real robots, and use results to guide architecture and training decisions