Join Us in Building the Future of Home Robotics
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.
What to ExpectYou are the bridge between raw data and robotic intelligence. As a Full Stack Engineer, ML Data & Evals, you will build the "Laboratory" where our ML team evaluates and deploys models. Your work accelerates the research-to-production loop, creating the infrastructure to launch on-robot evaluations and visualize model performance in complex, real-world scenarios.
What You’ll DoInteractive Data Systems: Architect the interfaces and engines that unify robot and Skill Capture Gloves™ data, enabling "human-in-the-loop" workflows, from episode annotation to seamless switching between autonomous execution and manual teleoperation intervention.
Evaluation & Benchmarking: Develop high-performance tools to compare model-driven motion against human-captured ground truth, helping quantify model progress across diverse tasks.
Data Processing & Orchestration: Architect processing services that transform raw captures and sensor data into ML-ready formats, ensuring a seamless flow from our global collection systems to the models that power our robots.
Startup Fluidity: While this role focuses on the ML Platform, our Full Stack Engineers are comfortable shifting priorities and domains, eager to jump into other parts of the stack as we scale.
Full-Stack Proficiency: 3+ years of building and scaling cloud-native applications with mastery of modern frontend (e.g., React, TypeScript) and robust backend (e.g., Node.js, Python) stacks.
Operational Mindset: Experience building high-throughput internal tooling or "human-in-the-loop" platforms.
Interactive ML Observability: A high bar for building low-friction interfaces that make complex model behaviors, sensor data, and "human-in-the-loop" interventions easy to interpret and act upon.
Experience as a founding or early hire; able to define roadmaps where no blueprint exists.
Experience building robust ETL pipelines that transform terabytes of multi-modal data into structured, high-quality datasets.
Familiarity with tools like Weights & Biases, MLFlow, or similar experiment tracking frameworks.
At Sunday Robotics, we’re building technology shaped by real people — curious, creative, and diverse. We’re proud to be an equal opportunity employer and consider all qualified applicants regardless of race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status.
Even if you don’t meet every single requirement, we encourage you to apply. Studies show that women and underrepresented groups often hold back unless they meet 100% of the criteria — we don’t want that to be the reason we miss out on great talent.
What We Do
Powered by state-of-the-art AI models and an ever-expanding Skill Library, Memo doesn't just know how to do a few tasks—Memo improves its skills faster than any robot that has come before it.
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