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HUD

Live runtime data for AI coding

Research Engineer - Robotics Evals

AI ResearchConfirmed live in the last 24 hours
Full-time

About the Job

Requirements

  • Experience in robotics, robot learning, embodied artificial intelligence, or closely related multimodal research.
  • Proficiency in Python and experience building data processing, analysis, or evaluation tools.
  • Experience translating research questions into dataset specifications, experiments, and measurable quality criteria.
  • Strong understanding of what makes robotics data useful for training or evaluation and where it can be misleading.
  • Attention to detail and ability to identify subtle errors, coverage gaps, and failure modes in complex data.
  • Experience building research tools or pipelines without a fully prescribed roadmap.

Responsibilities

  • Research the data needs of robot learning and physical artificial intelligence systems and translate them into concrete dataset and evaluation specifications.
  • Define data schemas, annotations, ground truth, and quality standards across robotics data types.
  • Design collection and review protocols that external data providers can execute reliably.
  • Build tools and validation workflows to audit datasets, identify quality issues, and give providers actionable feedback.
  • Run experiments and analyze model behavior to understand how data quality, coverage, and structure affect performance.
  • Work with research and engineering teams and, when needed, data vendors and buyers, to improve robotics data offerings.

Desired Qualifications

  • Experience working with robot trajectories, demonstrations, video, sensor data, simulation, or other multimodal robotics datasets.
  • Experience with imitation learning, reinforcement learning, or vision-language-action models.
  • Experience working in unstructured problem spaces and taking ownership from early research through production deployment.
  • Early-stage startup experience and communication skills for collaboration across teams and time zones.

About the Company

HUD

Live runtime data for AI coding

HUD builds a Runtime Code Sensor that links live production software with AI-powered coding assistants. Developers add a lightweight SDK to their apps to stream real-time information about how code behaves—such as errors, latency, performance, and how functions are used—directly to AI tools like GitHub Copilot and other code generators. The product works by feeding ongoing, context-rich data from a running system into AI models so generated code can be aware of real-world conditions rather than just static code. This makes AI-generated code safer and more reliable in production. HUD differentiates itself by enabling production-aware development, providing continuous feedback from live environments rather than relying on static analysis or old logs. The company’s goal is to help software teams build higher-quality software faster with fewer bugs and better performance by bridging the gap between AI-generated code and real-world usage.

Company size
51-200
Company stage
Early VC
Total funding
$21.2M
Headquarters
New York City, New York
Founded
2025

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