Data Operations Engineer
- Level
- Junior
- Work type
- On-site · San Francisco
Not stated in the posting: salary, visa.
Open. First seen 2 October 2026.
About the role
Specter's standard text
Company Background:
Specter's mission is to help automate the physical world.
Today, we build video sensors with state-of-the-art AI agents that answer any question, anywhere in their environments. Our systems can automatically detect and reason about any physical activity captured on camera, from security incidents (e.g. perimeter intrusion, theft, LPR), to safety monitoring (e.g. PPE detection, injured people), to operational efficiency (e.g. material tracking, congestion monitoring). We offer both long range wireless (1km range) and wired sensor variants to suit any deployment.
Our co-founders Xerxes and Philip are passionate about empowering our partners in the fast approaching world of physical AI and robotics. We are a small, fast growing team who hail from Anduril, Tesla, Uber, and the U.S. Special Forces.
Role:
Specter is hiring a data operations engineer to build our research data operation. This individual will own the full pipeline from defining what data we need, to getting it labeled at high quality, to ensuring it meets the needs of our research team and ultimately improves our models. The role sits at the intersection of engineering and research, with a focus on building systems and tooling.
Responsibilities:
- Own the end-to-end relationship with our data labeling provider, including task scoping, timeline management, and issue resolution
- Build and maintain internal tooling for labelers, including annotation interfaces, task pipelines, and dataset browsers
- Define and enforce quality control standards across all labeled data, implementing automated checks and audit workflows
- Partner with researchers to translate perception model needs into data collection strategies, identifying gaps in coverage across object types, scenes, lighting conditions, and sensor modalities
- Build dashboards and metrics to monitor dataset diversity, class balance, and domain coverage
- Close the loop on the data flywheel: track how labeled data flows into training, surface failure modes, and drive iteration on the pipeline from collection through to model improvement
- Evaluate and integrate new data sources
- Define labeling taxonomies and annotation specifications
Qualifications:
- 1-3+ years of experience in data operations, project management, or a technical coordination role, ideally supporting ML or engineering teams
- Proficiency in Python and comfort building lightweight tools, scripts, and dashboards
- Strong written and verbal communication skills, with experience managing external vendors or cross-functional stakeholders
- Familiarity with ML workflows and how training data impacts model performance
- Highly organized, with a track record of managing multiple concurrent workstreams
- Self-directed and autonomous
- Bonus: experience with computer vision data, annotation platforms, or labeling operations
What this role asks for
Particular to this role
Machine Learning
Rare in Specter's other 30 open postings.
Standard for software engineering roles
Python
Common in software engineering postings at any company.
70% of this description is written for the role. The rest is Specter's standard text, folded away below.
Read against Specter's other open postings on this site.
The team: Engineering HIRES STEADILY
This role is one of 22 open in Engineering. 2 were posted in the last 30 days and the oldest in October: a team that hires all year rather than one being built.
WHAT THE TEAM WORKS WITH, ACROSS ITS POSTINGS
Python (15 of 22), Embedded Systems (12 of 22), Linux (12 of 22), Computer Vision (8 of 22), Rust (8 of 22), Golang (6 of 22), C (5 of 22)
OTHER ROLES ON THIS TEAM
- Optics & Camera Engineering Lead posted Oct 16
- CV/ML Camera Test Engineer posted Oct 15
- Software Engineer - Applied AI posted Aug 28
- Software Engineer — Fleet posted Aug 24
- Platform Site Reliability Engineer posted Aug 20
- Hardware Test Engineer posted Aug 5
- Hardware Test Lead posted Aug 5
- Engineering Lab Manager posted Jul 14
- Engineering Technician posted Jul 14
- Fleet Reliability Engineer posted Jul 13
- Site Reliability Engineer posted Jul 2
- Software Engineer - Test Automation posted Mar 31
- Software Engineer - Embedded Systems posted Jan 23
- Software Engineer - Full Stack posted Jan 13
- RF Systems Engineer posted Nov 27
- Software Engineer - ML Infrastructure posted Oct 3
- Software Engineer - Systems posted Oct 3
- Software Engineer - Backend posted Oct 3
- Mechanical Engineer posted Oct 3
- Electrical Engineer posted Oct 3
- ML Research Engineer posted Oct 3
From the team and dates on Specter's own job board.
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