Senior Applied Scientist, Fauna

About the role

We are seeking an Applied Scientist to lead the development of evaluation frameworks and data collection protocols for robotic capabilities. In this role, you will focus on designing how we measure, stress-test, and improve robot behavior across a wide range of real-world tasks. Your work will play a critical role in shaping how policies are validated and how high-quality datasets are generated to accelerate system performance.

Responsibilities

• Design and implement evaluation frameworks to measure robot capabilities across structured tasks, edge cases, and real-world scenarios
• Develop task definitions, success criteria, and benchmarking methodologies that enable consistent and reproducible evaluation of policies
• Create and refine data collection protocols that generate high-quality, task-relevant datasets aligned with model development needs
• Build and iterate on teleoperation workflows and operator interfaces to support efficient, reliable, and scalable data collection
• Analyze evaluation results and collected data to identify performance gaps, failure modes, and opportunities for targeted data collection
• Collaborate with engineering teams to integrate evaluation tooling, logging systems, and data pipelines into the broader robotics stack
• Lead technical projects from conception through production deployment
• Mentor junior scientists and engineers

Qualifications

• PhD, or Master's degree and 6+ years of applied research experience
• 3+ years of industry or academic research experience
• Experience with any programming language such as Python, Java, C++
• 5+ years of building machine learning models or developing algorithms for business application experience
• Experience leading technical initiatives and key deliverables
• Experience in patents or publication at top-tier conferences
• Strong experience with robotics systems, control, or embodied AI
• Experience designing evaluation methodologies, benchmarks, or experimental frameworks for large-scale ML models or robotic systems
• Familiarity with teleoperation systems, simulation environments, or human-in-the-loop data collection