📋 Description

• Design, develop, and deploy ML/AI/GenAI solutions from concept to production.
• Build and optimize ML models for deep learning, NLP, forecasting, classification, regression, and
• Develop production-grade GenAI apps using LLMs, RAG, embeddings, retrieval optimization, reranking
• Design AI evaluation frameworks to assess quality, reliability, relevance, and performance.
• Build scalable AI services via REST and gRPC APIs and event-driven architectures.
• Establish and maintain MLOps and LLMOps practices across the lifecycle.

🎯 Requirements

• 8+ years of professional software engineering or technical engineering experience.
• Strong hands-on experience in Machine Learning and AI/ML Engineering.
• Advanced Python development with deep learning and ML techniques.
• Experience with NLP, forecasting, classification, regression, and anomaly detection.
• Proven experience building GenAI apps using LLMs and Retrieval-Augmented Generation (RAG).
• Knowledge of embeddings, retrieval tuning, reranking, prompt engineering, and AI/LLM evaluation

🎁 Benefits

• Opportunity to work on cutting-edge AI, machine learning, and GenAI solutions.
• Hands-on exposure to LLMs, RAG, MLOps, LLMOps, Kubernetes, and cloud-native practices.
• Collaborative environment with direct stakeholder engagement and impact.
• Competitive work environment with a focus on scalable, secure, observable AI systems.