Machine Learning Engineer – Intelligence

About the role

Join Oolka to build the core ML intelligence that powers our AI‑driven consumer fintech platform. You will lead model selection, design evaluation frameworks, and create a foundational retrieval and memory layer from first principles.

Key responsibilities

• Define and execute the model selection strategy for production AI systems.
• Design and implement 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 through post‑training techniques such as fine‑tuning and reinforcement learning.
• Drive research‑backed experimentation for continuous model improvement.
• Collaborate with product and engineering teams to translate ambiguous problems into robust ML solutions.
• Establish best practices for ML experimentation, evaluation, and deployment.

Required profile

• 3–5 years of experience in Machine Learning or Applied AI.
• Strong ML foundations with hands‑on work in XGBoost, NLP, recommendation systems, personalization, and large‑scale retrieval.
• Deep understanding of LLM architecture, training, inference, and post‑training (fine‑tuning or reinforcement learning).
• Experience designing model evaluation frameworks and benchmarking methodologies.
• Knowledge of retrieval systems, embeddings, ranking, and memory architectures.
• Ability to define ambiguous ML problems from first principles and drive independent solutions.
• Data‑driven experimentation mindset and excellent communication skills.

Required skills

• XGBoost
• Natural Language Processing (NLP)
• Recommendation systems
• Personalization
• Large‑scale retrieval
• LLM architecture, training, and inference
• LLM fine‑tuning
• Reinforcement learning for LLMs
• Model evaluation frameworks
• Benchmarking methodologies
• Embeddings
• Ranking systems
• Memory architectures