Description

Integrate Large Language Models and machine learning systems into production environments, focusing on scalable AI orchestration and model evaluation.

This role is on-site.

Responsibilities

• Develop, train, and deploy ML models optimized for production reliability and performance.
• Build AI orchestration pipelines to manage the end-to-end lifecycle of AI models, including deployment and scaling.
• Integrate Large Language Models (LLMs) into business applications using advanced prompt engineering and vector database strategies.
• Design embedding and chunking techniques for efficient data processing and information retrieval.
• Create automated feedback loops and evaluation metrics to continuously refine model accuracy using real-world data.

Required Skills

• 8+ years of experience in Machine Learning Engineering and building production-grade AI systems.
• Strong proficiency in Python and frameworks such as TensorFlow or PyTorch.
• Hands-on experience with LLM integrations, prompt engineering, and Text-to-SQL solutions.
• Deep understanding of Vector Databases (VectorDB) for storing and querying high-dimensional data.
• Proven ability to design model evaluation frameworks and implement feedback loop systems.
• Experience with cloud platforms (AWS) and containerization tools including Docker and Kubernetes.

Key Skills

Education

Any Gradute