Core Requirements
3–5 years of hands-on experience in AI/ML Engineering roles
Strong experience building and integrating solutions using LLM frameworks (LangChain, LlamaIndex, etc.)
Advanced proficiency in Python with strong command over data science libraries (Pandas, NumPy, Scikit-learn)
Practical experience with deep learning frameworks such as TensorFlow or PyTorch
Experience training and deploying ML models on cloud platforms (AWS, Azure, or GCP – GCP preferred)
Solid exposure to Generative AI and Large Language Models (LLMs)
Strong foundation in statistical modeling, machine learning theory, and data analysis
Experience containerizing applications using Docker and deploying ML models as APIs
Excellent communication skills with the ability to collaborate effectively across teams
Preferred Qualifications
Experience deploying models using API frameworks like FastAPI or Flask
Working knowledge of MLOps practices including CI/CD pipelines, model monitoring, and lifecycle management
Demonstrated AI/ML project portfolio or open-source contributions
Mandatory Skill Set
Deep Learning
AIOps
GenAI / LLMOps
Machine Learning (AIOps focus)
MLOps
Python (Data Science ecosystem)