Robotics Data Scientist

Job Description: Robotics Data Scientist (Contractor) Location : Hybrid -Redmond, WA Role Overview We are seeking a Robotics Data Scientist (Data collection)to support research in robot learning. This role focuses on training AI models that enable robots to perform various physical tasks by collecting, curating, and analyzing data through teleoperation. It’s a hands-on position ideal for students, early-career professionals, or self-taught candidates with technical curiosity and perseverance. Typical Day in the Role • Set up robots and teleoperation equipment in the lab • Follow structured data collection protocols • Collect and validate training data on physical robots • Run small-scale AI model training jobs • Evaluate and document model performance on robots • Collaborate with researchers to improve data collection processes Why This Role is Exciting • Work at the intersection of AI and robotics • See the immediate impact of your work on real robots • Gain hands-on experience with AI model training and teleoperation • Flexible work hours (~10 hours/week) • Potential to be credited on high-profile research publications Candidate Requirements • Experience: No formal years of professional experience required • Education: No degree required; high school students, undergraduates, or self-taught learners are welcome • Disqualifiers: Candidates who are unreliable or unable to commit due to the repetitive nature of tasks • Standout Traits: Evidence of perseverance, curiosity, and technical interest (Python, Linux, ML), even through personal projects Key Skills 1. Python – Minimum 2 years (academic, hobby, or self-taught experience acceptable) 1. Basic knowledge of computer science & machine learning concepts – Minimum 2 years 1. Ubuntu/Linux familiarity – Minimum 2 years (basic use acceptable) Additional Skills: • Familiarity with robotic manipulation • Strong written and oral communication • Troubleshooting and problem-solving abilities Assessment Process • Format: One remote interview (via Teams) • Focus Areas: Python, machine learning basics, data handling concepts • Preparation: Candidates should refresh Python skills and review teleoperation/data handling fundamentals Job Responsibilities • Collect AI training data by teleoperating a robotic manipulator • Verify and analyze collected data with the research team • Suggest improvements to data collection protocols • Run training jobs to evaluate data quality