Machine Learning Engineer

We are looking for an ML Engineer to design, prototype, research, and build AI systems. This is a high-impact role where you will not only write production-grade code but also improve the quality of a RAG-as-a-service platform. You will work on advanced concepts like Multilinguality, Self-Supervised Learning, and Agentic Behavior.

Key Responsibilities

• AI System Development: Train, evaluate, and deploy ML models in Natural Language Processing (NLP), Information Retrieval, AI Agents, and Multimodal Large Models (MLMs).
• RAG Optimization: Improve the company's RAG platform, focusing on hallucination reduction, multilinguality, and reasoning capabilities.
• End-to-End ML: Manage the full lifecycle of ML systems, from data curation to evaluation and deployment.
• Research & Publication: Publish technical blogs, research papers, and patents, contributing to the broader AI community.
• Collaboration: Collaborate effectively with cross-functional teams to integrate AI solutions.

Requirements

• Education & Experience: BS/MS in CS, Statistics, or Math with 4+ years of experience, OR a PhD with 1+ year of industry experience.
• Deep Learning Stack: Familiarity with Transformers, Retrieval-Augmented Generation (RAG), and Mixture of Experts (MoE).
• Technical Skills: Proficiency in data/ML libraries such as pandas, transformers, and torch.
• Retrieval Expertise: Expertise in embedding models, rerankers, multimodal retrieval, Vector Databases, and BM25.
• LLM Knowledge: Skilled in planning and reasoning in LLMs, NLG evaluation, and hallucination detection.

Nice to Have

• Research Pedigree: Publications in top-tier venues such as ACL, NeurIPS, ICML, or ICLR as a key author.
• Startup Grind: Experience working as an ML engineer in an early-stage, high-growth environment.