About the job
Qualcomm Robotics is shaping the future of intelligent machines. We are looking for a Robotics AI Engineer to help build next generation Vision Language Action (VLA) models. AI systems that enable robots to understand the world, follow natural language instructions, and perform complex tasks. This role combines cutting edge research with practical deployment on Qualcomm’s advanced robotics platforms.
Responsibilities
Research the latest trends in robotics AI and multimodal learning to inform Qualcomm’s VLA roadmap.
Design and develop models that connect vision, language, and action for real world robotic applications.
Build and maintain training pipelines, datasets, and evaluation benchmarks for embodied AI.
Optimize and deploy models on Qualcomm’s robotics platforms for realtime, ondevice performance.
Collaborate with crossfunctional teams to integrate AI capabilities into Qualcomm’s Robotics SDK and partner solutions.
Contribute to internal knowledge sharing and, where appropriate, publish findings in top AI and robotics venues.
Qualifications
Minimum
• Bachelor's degree in Computer Science, Engineering, Information Systems, or related field and 8+ years of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience.
OR
Master's degree in Computer Science, Engineering, Information Systems, or related field and 7+ years of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience.
OR
PhD in Computer Science, Engineering, Information Systems, or related field and 6+ years of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience.
Preferred
Master’s degree in Computer Science, Robotics, Electrical Engineering, or related field (PhD preferred).
Strong experience in deep learning (transformers, multimodal models) and robotics AI.
Proficiency in Python and frameworks like PyTorch or TensorFlow.
Familiarity with robotics systems, simulation environments, and ROS 2.
Experience with model optimization and deployment on edge or embedded platforms.
Background in vision-language models, policy learning, or robotic foundation models.
Experience with dataset curation, teleoperation data, or simulationtoreal transfer.
Knowledge of model compression techniques (quantization, distillation) for efficient deployment.
Strong communication skills and ability to work in a collaborative, fastpaced environment.