Remote Network Data Engineer for AI Systems

mercor

San Francisco (CA)

Ibrido

CAD 98.000 - 137.000

Part-time

14 giorni+
Generatore di candidature

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Descrizione del lavoro

Mercor is seeking a Network Engineer for remote engagement to support data labeling and analysis for autonomous systems. The role emphasizes hands-on work with enterprise networks, Wi‑Fi technologies, and real-time data streams, all delivered contractually on a 30–40 hour weekly basis.

You will review network data, classify behaviors, and help define data schemas used by downstream ML models, collaborating with the client team to ensure accuracy and timely delivery.

Competenze

  • Current role at Level 3 / Tier 3 / Principal Support Engineer level.
  • Experience with end-customer enterprise networks (switches, APs, firewalls).
  • Proficiency in Wi‑Fi/wireless, including Cisco WLC, Aruba, or Meraki.
  • Skills in packet-level troubleshooting using Wireshark, tcpdump, and SPAN captures.
  • Authorization to work in the US or Canada without sponsorship.

Mansioni

  • Review real-world data from deployed networks, including logs, configs, telemetry, and event streams.
  • Label and classify network behaviors, issues, anomalies, and incident patterns.
  • Define schemas and structure for large-scale data pipelines that downstream ML models will train on.
  • Interface directly with the client team to ensure data accuracy and relevance.
  • Work independently and asynchronously to meet deadlines while improving AI model performance.

Conoscenze

Senior level support engineer
Enterprise networks
Wi-Fi/Wireless
Packet capture
US/Canada work authorization

Strumenti

Cisco WLC
Aruba
Meraki

Descrizione del lavoro

Mercor is seeking a Network Engineer for remote engagement to support data labeling and analysis for autonomous systems. The role emphasizes hands-on work with enterprise networks, Wi‑Fi technologies, and real-time data streams, all delivered contractually on a 30–40 hour weekly basis.

You will review network data, classify behaviors, and help define data schemas used by downstream ML models, collaborating with the client team to ensure accuracy and timely delivery.

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