Humble Robotics
Data Engineer
San Francisco
Work authorization requiredDetected 92 days ago
RESTLogisticsRobotics
About the role
- About Humble Robotics Working at Humble Robotics means taking on the biggest change in ground transportation in decades.
- We don't believe culture can be engineered - but when it falls into place, it's a once-in-a-lifetime adventure.
- You'll work across the full lifecycle of our data, from ingestion to the point it gets pulled into a training run, and your work will directly shape how quickly the rest of the team can iterate.
Requirements
- Contact **legal@humblerobotics.ai** to exercise this right or if you have further questions on the use of AI tools in our hiring process.
Compensation
- This role is eligible for base salary + benefits + equity compensation.
- Salary ranges are determined by role, level, and location.
- Within the range, individual pay is determined by additional factors, including qualifications, skills, experience, and location.
- As part of the interview process, we may use Artificial Intelligence (AI) tools to compare your qualifications and experience to the job description.
- A human reviews all AI output and makes a final hiring decision.
- Humble Robotics does not rely on the output to make any employment decisions.
Benefits
- We're building an autonomous, zero-emissions hauler that dramatically lowers the cost of freight with groundbreaking vision-based AI, designed for today's global logistics network.
Company info
- We're looking for a data engineer to help us turn raw driving data into the well-structured, queryable, and trustworthy datasets that power our autonomy stack.
- Some applicants may have a legal right to opt-out of the use of AI as part of our interview process.
Equal opportunity
- Humble Robotics is an equal opportunity employer.
- equal opportunity employer.
Visa & Work Authorization
- Some applicants may have a legal right to opt-out of the use of AI as part of our interview process.
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This listing is sourced directly from Humble Robotics's careers page and normalized into a canonical job model.