Firststage

Overview

We are looking for a Research Scientist to join the Multi-Embodiment Generalist Agent (MEGA) team within Wayve Science as a founding member to build foundation models for general-purpose robots.

About Firststage

Founded in 2017, Wayve is the leading developer of Embodied AI technology. Our advanced AI software and foundation models enable vehicles to perceive, understand, and navigate any complex environment, enhancing the usability and safety of automated driving systems.

Requirements & Eligibility

• Experience in machine learning, with focus in multimodal foundation models and data for foundation models.
• Experience with scalable training, such as multi-node training, large datasets and/or large model training.
• Strong research track record, including publications in top-tier venues such as ICRA, CoRL, CVPR, NeurIPS, ICML or ICLR.
• Strong engineering skills and hands-on experience with modern machine learning frameworks.
• Ability to design and run rigorous experiments while collaborating closely with engineering and robotics teams.
• Experience translating research ideas into working systems, experiments or deployed capabilities.
• Strong communication skills and the ability to share research clearly across teams

Key Responsibilities

• Research and develop model architectures, learning objectives, and data strategies for robot foundation models.
• Empirical research experience – experience hill climbing on ML models.
• Experience with various data sources – annotation, filtering, mixing strategies.
• Develop scalable self-supervised and generative pre-training methods using web video, egocentric video, and robot-interaction data.
• Develop post-training approaches—including supervised fine-tuning, imitation learning, reinforcement learning, and related methods—to improve real-world robot capabilities.
• Curate, filter, and evaluate large-scale robotics datasets, including egocentric, UMI, and teleoperated data.
• Build and use distributed training pipelines for large models and large multimodal datasets.
• Work closely with robotics and hardware teams to connect model progress to measurable real-world performance.