Robotics Data & Evaluation Engineer – Remote-friendly

HUD; United States; Hybrid; USD 135,000 - 230,000; Full time

Benefits offered by this job

Medical coverage

Dental & Vision

Lunch & dinner

Holiday break

401k

Commuter benefits

Equinox membership

Token access

Job summary

HUD is seeking a Research Engineer for the Robotics team to design datasets and evaluations that advance embodied AI systems. You’ll translate open-ended research needs into data specifications, build validation tools, and run experiments to understand how data shapes model performance.

You’ll collaborate with researchers, engineers, and data vendors to improve robotics data offerings and ensure high-quality, scalable datasets for training and evaluation.

Qualifications

• Experience in robotics, robot learning, embodied AI, or related multimodal research.
• Proficiency in Python and data processing, analysis, or evaluation tooling.
• Ability to convert research questions into dataset specs, experiments, and quality criteria.
• Understanding of data usefulness and potential biases in robotics datasets.

Responsibilities

• Research data needs of robot learning and translate to concrete dataset specs.
• Define schemas, annotations, ground truth and quality standards.
• Design data collection/review protocols for external providers.
• Build tools and validation workflows to audit datasets and provide feedback.
• Run experiments to analyze how data quality affects model performance.
• Collaborate with HUD teams, data vendors, and buyers to improve offerings.

Skills

Robotics data

Python

Data processing

Experiment design

Quality analysis

Communication across teams

Tools

Pandas

NumPy

ROS

Experiment tracking tools

Job description

HUD is seeking a Research Engineer for the Robotics team to design datasets and evaluations that advance embodied AI systems. You’ll translate open-ended research needs into data specifications, build validation tools, and run experiments to understand how data shapes model performance.

You’ll collaborate with researchers, engineers, and data vendors to improve robotics data offerings and ensure high-quality, scalable datasets for training and evaluation.