# Data Infrastructure Engineer at Pivot Robotics

> Onsite · United States · Unspecified · DevOps / SRE / Infra · open. Source: https://alderhq.app/jobs/ashby%3Apivotrobotics%3A408c6c35-d819-4f4e-8fa4-8586f71916a5 (read 2026-11-05).

## Facts (observed)

- Company: [Pivot Robotics](https://alderhq.app/companies/pivot-robotics)
- Location text: San Francisco
- Where it can be done from (inferred): Onsite · United States (evidence: "Location: San Francisco")
- Posted: 2026-08-25 (72 days ago)
- First seen by alder: 2026-11-02 · last verified: 2026-11-03
- Reposted: 0 times · edited: 0 times
- Apply on the employer's site: https://jobs.ashbyhq.com/pivotrobotics/408c6c35-d819-4f4e-8fa4-8586f71916a5
- Skills listed (inferred): AWS, Distributed systems

## Pay and sponsorship

- Posted pay: not posted
- Market band for similar posted roles (SF Bay Area, n 158): p25 $200k, median $239k, p75 $309k

## Description (the employer's text)

### Responsibilities

Design and own the schemas and data models behind our production systems

Build and maintain data infrastructure on AWS

Build the artifact store for scans, meshes, model checkpoints, and calibration files

Build edge-to-cloud pipelines between robotic cells and our infrastructure

Build ML infrastructure: training pipelines, dataset versioning, and model deployment

### Requirements

2+ years building data infrastructure on AWS (application-side, not platform operations)

Strong schema design and data modeling, including distributed systems tradeoffs

ML infrastructure experience

Ability to work across the stack, from analyzing data to designing the systems around it

Willingness to travel to customer sites

### Preferred

Data infrastructure in a robotics, autonomy, or industrial IoT setting

Edge computing experience

Interest in manufacturing

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Data: alder (https://alderhq.app). Cite https://alderhq.app/jobs/ashby%3Apivotrobotics%3A408c6c35-d819-4f4e-8fa4-8586f71916a5 and the date you read it. Observed facts come from the employer's own listing; location reach, level, family and skills are inferences.