Lead Machine Learning Engineer

AI / AIOps Technical Lead

Experience: 6 12 Years

Role Overview

This isnt a just build models role. Youll lead AIOps innovation, owning research, architecture, and delivery of AI-driven solutions for IT operations. Expect a mix of hands-on work, team leadership, and real problem-solving (not just slide decks).

Must-Have Skills

• 6+ years overall experience with 5+ years in AI/ML (hands-on)
• Strong expertise in Machine Learning & Deep Learning, Natural Language Processing (NLP) & Generative AI & Large Language Models (LLMs)
• Proven experience building and deploying AI/ML models in production
• Hands-on experience with AIOps use cases:
• Anomaly detection
• Predictive maintenance
• Incident correlation & root cause analysis
• Strong programming skills (Python + ML ecosystem)
• Experience with ML frameworks:
• TensorFlow / PyTorch / Scikit-learn
• Solid understanding of MLOps practices (model deployment, monitoring, lifecycle)
• Strong technical leadership experience (mentoring, guiding teams)
• Ability to design scalable, production-grade AI systems
• Strong problem-solving and debugging mindset

Good-to-Have Skills

• Experience with Agentic AI / autonomous systems
• Hands-on exposure to Databricks
• Experience with cloud AI services (AWS, Azure, GCP)
• Familiarity with AIOps platforms/tools
• Experience working in R&D or innovation-driven environments
• Understanding of DevOps / IT operations workflows
• Advanced degree (Masters / PhD in relevant field)

Key Responsibilities

• Lead R&D initiatives for AI-driven AIOps solutions
• Design and implement systems for:
• Predictive maintenance
• Anomaly detection
• Incident management automation
• Drive adoption of Generative AI & LLMs for IT operations
• Own end-to-end AI project delivery
• Mentor and scale a team of AI/ML engineers and researchers
• Collaborate with product, engineering, and business teams
• Define AIOps strategy, roadmap, and innovation goals

Skills

Python, Artificial Intelligence, Machine Learning