Mercor - 277 Jobs
Toronto, ON
Posted 6 days ago
Job Details:
Remote
$50.00 - $70.00 / hour
Full-time
Entry Level
About the job
Mercor connects elite creative and technical talent with leading AI research labs. Headquartered in San Francisco, our investors include Benchmark, General Catalyst, Peter Thiel, Adam D'Angelo, Larry Summers, and Jack Dorsey.
Position: Network Engineer - Data for Autonomous Systems annotation
Type: Contract
Compensation: $50–$70/hour
Location: Remote
Commitment: 30–40 hours/week
Role Responsibilities
- Review real-world data from deployed networks, including logs, configs, telemetry, and event streams.
- Label and classify key behaviors, issues, and anomalies in network data.
- Help define schemas and structure for large-scale data pipelines.
- Interface directly with the client team to ensure data quality and relevance.
- Work independently and asynchronously to meet deadlines and improve AI model performance.
Qualifications
Must-Have
- Experience working as a network engineer, ideally with enterprise networks (switches, APs, firewalls, etc.).
- Comfort with interpreting logs, events, and time-series metrics.
- Curiosity about how raw infrastructure data becomes machine learning input.
Application Process (Takes 20–30 mins to complete)
- Upload resume
- AI interview based on your resume
- Submit form
Resources & Support
- For details about the interview process and platform information, please check: https://talent.docs.mercor.com/welcome
- For any help or support, reach out to: [email protected]
PS: Our team reviews applications daily. Please complete your AI interview and application steps to be considered for this opportunity.
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Frequently Asked Questions
Compensation is $50.00–$70.00 per hour for this contract role.
This is a remote contract role, with location listed as Toronto, ON.
The role requires about 30–40 hours per week.
Responsibilities include reviewing real-world data from deployed networks, labeling and classifying behaviors and anomalies, helping define schemas for large-scale data pipelines, interfacing with the client team, and working independently to improve AI model performance.
Must have experience as a network engineer with enterprise networks, comfort interpreting logs and time-series metrics, and curiosity about turning raw infrastructure data into machine learning input.
The process includes uploading your resume, an AI interview based on your resume, and submitting a form.
