Machine Learning Engineer

Position Overview

The Machine Learning Engineer will focus on designing, developing, and deploying AI and machine learning solutions that address IT and network operational challenges. As the AI Solutions Owner, the role includes establishing the AI automation roadmap aligned with strategic objectives, architecting scalable AI frameworks for network diagnostics, and integrating large language models (LLMs) to enhance network operations and automation.

Key Responsibilities

• Develop and execute a strategic AI-driven automation roadmap supporting company and client objectives.
• Work closely with engineering and data teams to build scalable and innovative AI applications, such as network diagnostic tools and AI agents for network operations center (NOC).
• Function as the Agile Scrum Solution Owner, managing product backlogs, writing detailed user stories, and prioritizing development efforts.
• Lead assessment, refinement, and integration of open-source LLMs like the Llama series alongside proprietary models.
• Create and maintain core components of automation pipelines using PowerShell and Python runbook executors.
• Design, train, and optimize machine learning models focused on anomaly detection, predictive maintenance, and capacity forecasting within IT infrastructures.
• Process and analyze extensive IT operations datasets through cleaning, feature engineering, and analytics to enhance model precision.
• Develop internal automation tools and frameworks to improve operational efficiency.
• Continuously identify opportunities to improve service quality and operational processes.
• Build AI/Generative AI point solutions tailored to business requirements.
• Diagnose and fix issues related to automation frameworks and AI models.
• Collaborate intensively with customers, IT operators, network engineers, and other stakeholders to ensure solutions meet market needs.
• Provide expert knowledge on AIOps, IT process automation, and runbook automation while offering technical insights and guidance.
• Document all automation-related workflows, codes, and AI models clearly.
• Contribute actively to team goals and support skill development, including training junior members.

Qualifications and Skills

• Minimum 4 years of experience in IT services, with at least 3 years in IT service automation, orchestration, scripting, and process evaluation.
• Demonstrable experience in AI engineering, especially deploying AI agents and advanced ML/GenAI solutions to resolve complex business challenges.
• Proficient in scripting languages such as PowerShell, Python, and Shell scripting.
• Strong foundational knowledge in IT, focusing on networks and network services including topology, protocols, and operational challenges.
• Experience working with state-of-the-art LLMs, including open-source models like Llama series and proprietary ones like GPT-4.
• Competency in deep learning frameworks, preferably PyTorch, for experimental development and model fine-tuning.
• Programming skills in languages like Python and Java, with container deployment expertise using Docker and Kubernetes.
• Familiarity with cloud environments such as Microsoft Azure or Google Cloud Platform, including their networking components.
• Solid grasp of AI/ML libraries and ecosystem tools.
• Understanding of ITIL processes across service lifecycle or capability modules.
• Knowledge of systems administration tasks such as monitoring, incident and change management, and maintenance.
• Excellent communication skills to explain technical concepts effectively.
• Strong analytical and problem-solving abilities.