ML Engineer (Intelligence) - Bengaluru

Lead model selection strategy and design evaluation frameworks for production AI systems, focusing on LLM quality and performance.

Architect and build foundational retrieval and memory layers including scalable retrieval pipelines and ranking systems in an AI fintech environment.

Drive continuous model improvement using post-training techniques such as fine-tuning and reinforcement learning, supported by research-driven experimentation.

3–5 years of experience in Machine Learning or Applied AI.

Strong expertise in ML foundations with hands-on experience in XGBoost, NLP, recommendation systems, personalization, large-scale retrieval, and deep understanding of LLM architecture and inference.

Mandatory experience with LLM post-training techniques including fine-tuning and/or reinforcement learning approaches.

Location: Bengaluru (onsite requirement).

Experienced ML Engineer skilled in designing and implementing evaluation frameworks and benchmarking methodologies for large AI models.

Comfortable solving ambiguous ML problems from first principles and independently driving solutions with a data-driven experimentation mindset.

Familiar with building retrieval systems, embeddings, ranking, and memory architectures in a production fintech AI context.