Overview

This opportunity with Aurionpro Solution Ltd; for the below position :

Responsibilities

• Deliver AI initiatives across product lines, including framework upgrades for existing JavaScript-based systems.
• Build customer segmentation and predictive models using ML algorithms.
• Develop and deploy FastAPI-based AI services, microservices, and integration layers.
• Manage the end-to-end LLM lifecycle, including model selection, fine-tuning, prompt engineering, RAG, vector database setup, and performance optimization.
• Automate business processes using AI-driven workflows and orchestration.
• Contribute to new AI product development and integrate intelligent features into existing platforms.
• Build and maintain scalable data pipelines, feature engineering processes, and ML model monitoring systems.
• Evaluate open-source and commercial AI/ML/LLM tools for adoption within the product ecosystem.
• Implement AI governance, security controls, and compliance standards.
• Collaborate with engineering, product, and business teams to translate requirements into working AI solutions.
• Support the creation and maintenance of the overall AI strategy, roadmap, and execution plan.
• TensorFlow
• PyTorch
• Scikit-learn
• MLflow – self-hosted experiment tracking
• ONNX Runtime – offline inference
• Hugging Face open-source models – self-hosted/offline
• Customer churn prediction
• RFM and customer segmentation
• K-Means, DBSCAN, GMM, Hierarchical Clustering
• Recommendation systems – collaborative and content-based filtering
• Propensity models using XGBoost, LightGBM, Random Forest, and Logistic Regression
• NLP – tokenization, embeddings, sentiment analysis
• Deep learning for pattern detection and advanced modeling
• Customer behavior simulations based on event streams
• Agent-based and scenario-based predictive modeling
• Time-series forecasting using ARIMA, LSTM, Prophet, and Transformers

Qualifications

• 5 years of experience in AI/ML Engineering, LLM Development, or Applied AI roles.
• Hands-on experience with Python, FastAPI, ML frameworks, and data science toolkits.
• Strong understanding of JavaScript-based product ecosystems and modern framework upgrade approaches.
• Experience working with multiple LLM tools, including local models, cloud APIs, and open-source models.
• Strong knowledge of RAG, vector databases, embeddings, and prompt engineering.
• Solid understanding of MLOps, including model lifecycle, versioning, deployment, and monitoring.
• Ability to contribute to AI strategy, architecture, and scalable enterprise AI systems.
• Strong analytical, communication, and cross-functional collaboration skills.