Machine Learning Research Engineer/Scientist
As a Machine Learning Research Engineer at Sunday Robotics, you will develop state-of-the-art robot learning algorithms for dexterous manipulation and controls in home environments. You will leverage large-scale data collection to create generalizable robot behaviors and own the end-to-end process from task definition to on-robot deployment. This role involves close collaboration with a full-stack robotics team to advance embodied AI for consumer personal robots.
At Sunday, we're developing personal robots to reclaim the hours lost to repetitive tasks. We're focused on an ambitious goal to make generalized robots broadly accessible, enabling households to take back quality time. We have spent the last 18 months building a talented team, securing capital, and validating our technology. We are now seeking passionate individuals to join us in the next phase of our growth. If you are ready to apply your skills to the forefront of robotics innovation, we’d love to hear from you.
In building robots for the home, we are tackling a true grand challenge in robotics: dexterous and safe mobile manipulation in unstructured environments. To make this possible, we are building across the entire robotics stack. We’re training state-of-the-art AI models that leverage our large-scale, high-quality, real-world data collection system. At the same time, we’re building a new kind of consumer hardware product, which will be deployed into homes and delivering real value for real customers. As an early member of a small, cross-functional team, you’ll play a key role in pushing both our technology and product forward: advancing the frontier of embodied AI, and soon giving countless hours back to our customers so they can spend more time on the things they value most.
As a Machine Learning Research Engineer, you will work on the software and algorithms that enable our robots to complete dexterous manipulation tasks in home environments. You will leverage our unique large-scale in-the-wild data collection operation and our growing robot fleet to continuously add new behaviors and improve robustness across tasks and environments.
Posted June 2, 2026