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ML Engineer (Intelligence) - Bengaluru

CLANX
Bengaluru, IND
Full-time
Onsite
Discovered 1 months ago
machine learningapplied AIXGBoostnatural language processingrecommendation systemspersonalization

Full Job Posting

Role Overview

Build Oolka’s core machine learning intelligence by leading model selection, evaluation frameworks, and the retrieval and memory layer for AI systems.

This is a research-driven ML Engineering role focused on first-principles problem solving.

About Oolka

Oolka is an AI-powered consumer fintech company focused on helping users improve and manage their credit health with AI.

ClanX is a recruitment partner supporting Oolka’s ML Engineering hiring.

Requirements

  • 3–5 years of experience in machine learning or applied AI.
  • Strong ML foundations with hands-on experience in XGBoost, NLP, recommendation systems, personalization, and large-scale retrieval.
  • Deep understanding of LLM architecture, training, and inference.
  • Mandatory LLM post-training experience through fine-tuning and/or reinforcement learning.
  • Experience designing model evaluation frameworks and benchmarking methodologies.
  • Strong knowledge of retrieval systems, embeddings, ranking, and memory architectures.
  • Ability to define ambiguous ML problems from first principles and independently drive solutions.
  • Strong experimentation mindset, data-driven decision making, communication, and technical reasoning.

Responsibilities

  • Own model selection strategy for production AI systems.
  • Design and build evaluation frameworks for LLM quality and performance.
  • Architect and build Oolka’s retrieval and memory layer from scratch.
  • Develop scalable retrieval pipelines and ranking systems.
  • Improve model quality with fine-tuning and reinforcement learning approaches.
  • Drive research-backed experimentation for continuous model improvement.
  • Translate ambiguous problems into robust ML solutions with product and engineering teams.
  • Establish best practices for ML experimentation, evaluation, and deployment.

Interview Process

  • The interview process includes recruiter screening, a hiring manager discussion, an ML deep dive, system design and problem solving, and a founder round.

Location

  • The listed role location is Bengaluru.
  • The source does not explicitly state whether the role is remote, hybrid, or onsite.

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