About The Position

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. You are the bridge between raw data and robotic intelligence. As a Full Stack Engineer for ML Systems, you will build the "Laboratory" where our ML team trains, evaluates, and deploys models. Your work accelerates the research-to-production loop, creating the infrastructure to launch large-scale experiments and visualize model performance in complex, real-world scenarios.

Requirements

  • Full-Stack Proficiency: Expert-level TypeScript/Python and React.
  • 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.

Nice To Haves

  • 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.

Responsibilities

  • Interactive Training Systems: Architect the interfaces and engines that unify robot and Skill Capture GlovesTM 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 develop model performance 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, we operate in a high-growth environment. You should be comfortable with shifting priorities and jumping into other parts of the stack as we scale.
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