Network Engineer - Data for Autonomous Systems annotation
Listing checked August 15, 2026 · pay as published by Mercor
Overview
Meter's client needs Tier 3 network support engineers to turn real production network data into structured training input for AI models. The work applies your existing escalation, RCA, and packet-analysis experience in a different way: labeling and annotating logs, configs, telemetry, and event streams from deployed enterprise networks. You'll bring hands-on familiarity with Wireshark, tcpdump, and enterprise WLAN systems to help define schemas for downstream machine learning. The role suits maintainers rather than designers or architects. Applications move through a rolling talent network, with periodic interview rounds as headcount opens.
What You'll Do5
- 1Examine production network logs, configuration files, telemetry feeds, and event streams from active client deployments.
- 2Tag and categorize observed network behaviors, fault conditions, anomaly signatures, and incident patterns.
- 3Design and document labeling schemas for large-scale data pipelines that downstream ML models will consume.
- 4Cross-check labeled data against known escalation cases and root cause analyses to improve accuracy.
- 5Collaborate with client engineers to clarify ambiguous network states and edge cases during labeling.
Requirements6
- 1Current or recent position as a Level 3, Tier 3, or Principal Support Engineer with production incident escalation duties, on-call rotation, and RCA ownership.
- 2Hands-on experience troubleshooting enterprise networks built with switches, access points, and firewalls across sectors such as retail, healthcare, finance, manufacturing, education, and hospitality.
- 3Working proficiency with enterprise WLAN controllers from Cisco, Aruba, or Meraki, including 802.1X and RADIUS authentication.
- 4Ability to capture and interpret packets using Wireshark, tcpdump, or SPAN port configurations.
- 5Familiarity with how raw infrastructure data is structured for use in machine learning pipelines.
- 6Authorization to work in the United States or Canada without sponsorship.
Who Should Apply
The ideal candidate lives in the escalation queue today and can point to specific RCA or outage cases where packet captures changed the outcome. This role suits people who want to keep their hands on real network operations while shifting part of their energy to data curation for AI. Architects, cloud/SRE specialists, security analysts, and helpdesk staff will find a poor fit because the work centers on maintaining and interpreting existing infrastructures. Candidates get screened out when they claim wireless experience but cannot speak to 802.1X or controller-level debugging, or when they have only opened Wireshark occasionally instead of using it for deep packet analysis.
Salary Insight
The pay range is $50-$70 per hour, paid as a 1099 contract to a personal account, with no corp-to-corp arrangement. That rate aligns with the senior support level and the required depth in wireless troubleshooting and packet analysis. The client confirms the exact rate when a headcount round opens.
Pay and demand for Data Engineering roles
AggregatedTypical pay
$70/hour
This role
$50–$70/hr
Most Data Engineering roles pay $40–$95 per hour. This role's pay falls inside that range.
Based on 1,030 similar roles that publish pay · 300 publish only a top rate; those count at the rate they gave
Rates shown per hour. Yearly and monthly pay converted; one-time fees and non-USD pay are not included.
- Live similar roles
- 1,196
- Listed in last 30 days
- 440
- Remote
- 97%
Hiring most right now: micro1 (333) · SME Careers (254) · Mercor (142)
Most requested skills · share of roles
- ai training13%
- ai evaluation12%
- llm evaluation11%
- data annotation9%
Figures from Data Engineering roles live on NearSkill when this page loaded. A role can close before you apply, so check the listing itself.
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Compensation
$50–70/hr
Required Skills
Application Tip
In your application, describe one outage you resolved using Wireshark or tcpdump, and name the exact wireless controller models you supported. Mention the scale of the environment, such as number of access points or sites, because the client needs evidence of production enterprise experience beyond lab setups.
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