---
title: 'Data Operations Engineer at Specter'
canonical: 'https://feeny.ai/job/data-operations-engineer-specter-san-francisco-006q5tchwhek'
type: 'job'
last_seen: '2026-10-12'
---

# Data Operations Engineer at Specter

- **Company:** Specter
- **Location:** San Francisco, CA
- **Employment:** full-time
- **Work type:** onsite
- **Posted:** 2026-05-20
- **Last confirmed live:** 2026-10-12
- **Apply:** https://jobs.ashbyhq.com/specter/af53e965-287d-4a18-9090-6e6302b4c78c

## Job description

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

## About Specter

## Company Overview
- **One-liner**: Specter builds and deploys long-range wireless sensing networks with AI-powered real-time alerts and semantic search, creating the perception layer for the physical world.
- **Entity Type**: Private (funding stage not publicly disclosed)
- **Headquarters**: Not publicly available (likely US based on website language and job postings)
- **Founded**: Not publicly available
- **Founders**: Not publicly available

## Core Business
- Primary industries: Physical security, critical infrastructure monitoring, industrial IoT, real-time situational awareness
- Target customers: Enterprise and government – including energy companies, data centers, construction firms, ports, stadiums, industrial facilities, and campuses
- Mission statement: "Creating a Software Defined Physical World" – providing instant awareness through real-time alerts, semantic search, and a map-based view of every event

## Products & Services
- **Specter Platform**: A SaaS-based physical intelligence platform that ingests data from long-range wireless sensors (video, thermal, acoustic) and applies general AI (natural language alerts) to detect events such as unauthorized access, safety hazards, equipment anomalies, fires, spills, and perimeter breaches. Features include semantic search, live and historical event detection, and complete situational awareness dashboards.
- **Long-Range Wireless Sensing Network**: Proprietary hardware and software for rugged, wide-area coverage without trenching – deployed across refineries, deserts, offshore platforms, construction sites, and other harsh environments.

## Market Standing
- **Valuation/Market Cap**: Not disclosed
- **Key Metric**: Annual revenue not publicly available; company is actively hiring (Software Engineer – Systems listing) and has a live product across multiple industry verticals.
- **Notable Investors/Partners**: Not publicly available
- **Growth Signals**: Recent website updates as of June 2026; expanding to new use cases (energy, data centers, construction, ports, stadiums); job openings indicate scaling engineering team.

## Competitive Advantages
- **Long-range wireless sensing** that eliminates blind spots without trenching or on-site personnel – a differentiator for remote and harsh environments.
- **General AI with natural language alerts** – users set and query alerts in plain English, lowering the barrier for security and operations teams.
- **Multimodal sensing** (video, thermal, acoustic) combined with real-time analytics for high-fidelity event detection (e.g., PPE compliance, spills, equipment theft, person-down incidents).
- Focus on **critical infrastructure** where downtime or security gaps carry high stakes, creating deep vertical-specific moats.

## Strategic Focus
- Expanding horizontal deployment across energy, data centers, construction, logistics, and campus security.
- Deepening AI capabilities through real-time semantic search and event detection to replace traditional CCTV monitoring.
- Building a “software-defined physical world” that unifies disparate sensors into a single intelligent layer.

## Why Work Here
- Opportunity to work on cutting-edge AI + IoT systems that monitor real-world infrastructure at scale.
- Engineering culture likely emphasizes distributed systems, computer vision, edge computing, and high-reliability software (based on job description for Software Engineer – Systems).
- Fast-paced startup environment with a clear product-market fit across multiple verticals.
- Remote/hybrid policy not explicitly stated; job posting does not specify location, but likely offers flexibility.

## Sources
1. [specter.co](https://specter.co/)
2. [specter.co/product](https://specter.co/product)
3. [specter.co/industries](https://specter.co/industries)
4. [specter.co/features](https://specter.co/features)
5. [jobs.ashbyhq.com - Software Engineer – Systems](https://jobs.ashbyhq.com/specter/fe26a690-7934-46f4-bce2-8d8c5495a0dc)

## Other roles at Specter

- [Founding Customer Operations Lead](https://feeny.ai/job/founding-customer-operations-lead-specter-san-francisco-4e0jb5pg08bh) — San Francisco, CA
- [Manufacturing Engineer](https://feeny.ai/job/manufacturing-engineer-specter-san-francisco-g75553wbxwx6) — San Francisco, CA
- [Wireless Software Engineer](https://feeny.ai/job/wireless-software-engineer-specter-san-francisco-zvjchm89fzv0) — San Francisco, CA
- [Software Engineer - Applied AI](https://feeny.ai/job/software-engineer-applied-ai-specter-san-francisco-p7er9310dx06) — San Francisco, CA
- [Senior Antenna Engineer](https://feeny.ai/job/senior-antenna-engineer-specter-san-francisco-xea2760wvrkw) — San Francisco, CA
- [Software Engineer — Fleet](https://feeny.ai/job/software-engineer-fleet-specter-san-francisco-5tm2vh5drfnf) — San Francisco, CA
- [Platform Site Reliability Engineer](https://feeny.ai/job/platform-site-reliability-engineer-specter-san-francisco-c9mhsvjd32qq) — San Francisco, CA
- [Founding Deployment Strategist](https://feeny.ai/job/founding-deployment-strategist-specter-san-francisco-81ba238x3y8m) — San Francisco, CA
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- [Hardware Test Engineer](https://feeny.ai/job/hardware-test-engineer-specter-san-francisco-0tgzpmm9kqx3) — San Francisco, CA