Principal Machine Learning Engineer

Role Overview

This is a senior-level technical leadership role focused on designing and scaling advanced Machine Learning and GenAI systems in a cloud-native environment. You will drive end-to-end AI solution development, from research and experimentation to production deployment and monitoring.

What You Will Do

Lead the design and development of end-to-end ML, GenAI, and Agentic AI solutions from ideation to production deployment and monitoring. Build and deploy machine learning models for cloud workload prediction, resource optimization, and intelligent automation use cases.

Why It Might Be a Fit

This position is ideal for someone who thrives in high-scale environments and enjoys turning cutting-edge AI into production-ready systems. You will have the opportunity to lead cutting-edge AI/ML initiatives with direct production impact and influence cloud optimization and intelligent automation at scale.

Requirements

• Bachelor’s, Master’s, or PhD in Computer Science, Machine Learning, Artificial Intelligence, or a related field.
• 10+ years of experience in Machine Learning, AI, or Data Engineering roles, with strong production-scale delivery experience.
• Proven track record of building and deploying ML systems in SaaS, cloud, or large-scale distributed environments.
• Strong hands-on expertise with Python and ML frameworks such as TensorFlow, PyTorch, or scikit-learn.
• Solid experience with cloud platforms (AWS preferred), infrastructure as code (Terraform), and data processing tools such as Spark and Databricks.
• Practical experience with GenAI, LLMs, and Agentic AI frameworks such as OpenAI, Hugging Face, or LangChain in production environments.
• Strong leadership, communication, and stakeholder management skills in cross-functional settings.

Benefits

• Opportunity to lead cutting-edge AI/ML initiatives with direct production impact.
• High-impact role influencing cloud optimization and intelligent automation at scale.
• Exposure to advanced GenAI, LLMs, and Agentic AI technologies in real-world applications.
• Collaborative, innovation-driven environment with cross-functional global teams.
• Competitive compensation package with performance-based rewards.
• Flexible work arrangements depending on team and project requirements.
• Professional growth opportunities in a fast-evolving AI and cloud technology landscape.