Senior Network Engineer | Upto $70/hr

## About the Role The Senior Network Engineer role at mercor represents a unique opportunity for network engineers to contribute to the development of cutting-edge AI models by working with real-world network data. This position involves reviewing extensive datasets from deployed networks, including logs, configurations, telemetry, and event streams, to label and classify key behaviors, issues, and anomalies. The role is crucial as it directly influences the quality and relevance of data used in AI model development, ensuring that the models are trained on accurate and meaningful data. In this role, you will be working closely with the client team to ensure data quality and relevance, requiring strong communication and interpersonal skills. The ability to work independently and manage your time effectively to meet deadlines in an asynchronous work environment is also essential. Given the nature of the work, a curiosity about how raw infrastructure data becomes machine learning input is not just beneficial but necessary. As a Senior Network Engineer, you will be part of a team that values innovation and excellence, with a commitment to leveraging technology to advance AI research. Your work will contribute to the development of autonomous systems, furthering the field and its applications.

## What You Will Do - Review real-world data from deployed networks to identify and classify network behaviors, issues, and anomalies.

• Label and categorize data accurately to ensure high-quality input for AI model development.
• Collaborate with the client team to define schemas and structure for large-scale data pipelines, enhancing data usability and relevance.
• Work directly with the client team to ensure data quality and relevance, addressing any concerns or issues promptly.
• Develop and maintain documentation of data annotation guidelines and best practices.
• Participate in the development of tools and scripts to automate data processing and annotation tasks.
• Contribute to the improvement of AI model performance by providing high-quality annotated data.
• Interface with various stakeholders to understand data requirements and provide insights on network data trends.
• Stay updated with the latest developments in network engineering and AI to continuously improve data annotation quality and relevance.

## What We Are Looking For - Experience working as a network engineer, preferably with enterprise networks (switches, APs, firewalls, etc.).

• Strong understanding of network protocols and architectures.
• Comfort with interpreting logs, events, and time-series metrics from network devices.
• Curiosity about how raw infrastructure data becomes machine learning input and a desire to contribute to this process.
• Ability to work independently and manage time effectively in an asynchronous environment.
• Excellent communication and interpersonal skills for effective collaboration with the client team.
• Familiarity with data annotation tools and methodologies.
• Basic understanding of machine learning concepts and their application in network engineering.

## Nice to Have - Experience with cloud-based network infrastructure and services.

• Knowledge of scripting languages such as Python for automating tasks.
• Familiarity with data pipeline tools and technologies.
• Experience with agile development methodologies and version control systems.
• Certification in network engineering or a related field.

## Benefits and Perks - Competitive hourly compensation ranging from $50 to $70 per hour.

• Opportunity to work with a leading company in AI research and development.
• Flexible, remote work arrangement with a commitment of 30-40 hours per week.
• Access to cutting-edge technologies and tools in network engineering and AI.
• Collaboration with a talented team of engineers and researchers.
• Professional development opportunities to enhance skills in network engineering and AI.
• Comprehensive support for remote work, including resources and tools for productivity and success.

- Develop a strong understanding of network engineering principles, including protocols, architectures, and device configurations, to effectively classify and annotate network data.

• Build a portfolio of your network engineering projects, highlighting your experience with enterprise networks and data annotation, to demonstrate your skills to potential employers.
• Stay updated with the latest trends in AI and machine learning, particularly in how they intersect with network engineering, to enhance your contributions to AI model development.
• Improve your communication skills to effectively collaborate with client teams and stakeholders, ensuring that data quality and relevance meet project requirements.
• Be prepared to discuss your experience with data annotation tools and methodologies, and how you approach ensuring data quality and relevance in your work.
• Show enthusiasm for the intersection of network engineering and AI, and be prepared to discuss how your role contributes to the development of autonomous systems and AI models.
• Negotiate your hourly rate based on your experience and the value you bring to the project, considering factors such as your expertise, the complexity of the work, and the demand for your skills in the market.