Requirements
- BS/MS in Computer Science, Statistics, Electrical/Computer Engineering, Mathematics, or related field.
- 7+ years of professional work experience after BS/MS applying machine learning to real-world problems, and crafting scalable and effective ML/AI solutions.
- Strong domain knowledge in at least one of the following: RAG, LLM, information retrieval, Multimodal LLMs.
- Excellent programming skills in Python. Proficiency in data/ML libraries such as pandas, transformers, and torch.
- Familiarity with the technical details of deep learning concepts, such as Transformers, Retrieval-Augmented Generation (RAG), mixture of experts (MoE).
- Hands-on experience in training ML systems end-to-end from data curation to evaluation and deployment.
- PhD in Computer Science/Engineering with 1+ years of industry experience.
- Publications in top-tier venues such as ACL, NAACL, EMNLP, NeurIPS, ICML, or ICLR as a key author.
- Experience as an ML engineer in an early-stage, high-growth environment.
- Expertise includes embedding models, rerankers, multimodal retrieval, question answering, reasoning, vector databases, and BM25.
- Skilled in planning and reasoning in LLMs, multilinguality in LLMs, and NLG evaluation, including hallucination detection.
Responsibilities
- Design, prototype, research, and build AI systems for the Company.
- Train, evaluate, and deploy ML models in Natural Language Processing, Information Retrieval, AI Agents, Large Language Models (LLMs), and Multimodal Large Models (MLMs).
- Improve the quality of the Company's AI Agents and RAG-as-a-service platform, including features such as agentic behavior, hallucination reduction/correction, and agent orchestration.
- Publish technical blogs, research papers, and patents.
Washington DC, United States of America
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JS26489_25303_56C20DF3C82836E790F538A8A2B7B0C8
1/23/2026 11:46:18 PM
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