BS or MS in Computer Science, Statistics, Electrical/Computer Engineering, Mathematics, or a related field, with 7+ years of professional ML experience applying ML to real-world problems and building scalable ML/AI solutions
Strong domain knowledge in RAG, LLMs, information retrieval, and multimodal LLMs; proficient in Python and ML libraries such as pandas, transformers, and PyTorch; familiarity with deep learning concepts including Transformers, RAG, and MoE
Hands-on experience training ML systems end-to-end from data curation to evaluation and deployment; experience as an ML engineer in an early-stage, high-growth environment
PhD in Computer Science/Engineering with 1+ year of industry experience and publications in top-tier venues (ACL, NAACL, EMNLP, NeurIPS, ICML, or ICLR) as a key author
Requirements:
Design, prototype, research, and build AI systems for the Company
Train, evaluate, and deploy ML models in NLP, Information Retrieval, AI Agents, LLMs, and Multimodal LLMs
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
Job description
Requirements:
BS/MS in Computer Science, Statistics, Electrical/Computer Engineering, Mathematics, or a 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.
