We are looking for a Machine Learning Engineer who excels at turning AI research into scalable, production-grade reality. You will be responsible for the 'heavy lifting' building the frameworks that allow our AI models to reason, the pipelines that feed them, and the infrastructure that ensures they are fast, ethical, and cost-efficient. You will bridge the gap between Data Science prototypes and enterprise-scale deployment.
Key Responsibilities
AI Model design and build: Work closely with data scientists and business to design and implement AI algorithms,
frameworks and architectures.
AI model Data Preprocessing: Design, build, and maintain robust ETL/ELT pipelines to ingest, transform, and load
data from various sources.
AI model Feature Engineering: Integrate structured and unstructured data from internal and external systems into
centralized data platforms.
Performance Tuning of AI/ models: Optimize data workflows and queries for performance, scalability, and
cost-efficiency. Building Agentic Systems: Developing intelligent AI agents that can reason, plan, and execute tasks
autonomously using LLMs and other tools.
LLM application Development: LLM fine-tuning adapting pretrained LLMs for specific tasks using techniques like
parameterefficient fine-tuning (PEFT) (e.g., LoRA, QLoRA). Implementing Retrieval-Augmented Generation
pipelines to enhance...