Applied Scientist

We are seeking an experienced Applied Scientist to drive research and development in Large Language Models (LLMs) and machine learning systems for business applications. The ideal candidate will have a strong background in AI research, practical experience deploying ML models, and a proven track record of impactful publications and/or industry contributions. Responsibilities Design, develop, and deploy machine learning models for business applications. Conduct research on LLMs, including pre-training, fine-tuning, and application of reasoning, agentic, synthetic, or organic data. Translate research breakthroughs into production-grade, scalable AI systems. Collaborate with cross-functional teams to integrate AI solutions into business workflows. Contribute to the AI research community through publications in top-tier conferences and journals. Stay at the forefront of AI advancements, particularly in generative AI, Transformers, reinforcement learning, and state-of-the-art NLP/Computer Vision techniques. Basic Qualifications PhD in Computer Science, Computer Engineering, AI, ML, or related field, or a Master’s degree with 6+ years of relevant experience. 5+ years of experience building machine learning models for real-world business applications. Strong programming skills in Python, Java, C++, or similar languages. Practical experience with LLM pre-training, fine-tuning, or application. Experience handling diverse data types for LLMs, including organic, synthetic, reasoning, or agentic data. Professional software development experience in Unix/Linux environments. Published research in top AI conferences ("e.g., NeurIPS, ICML, ICLR, ACL, EMNLP, NAACL") or demonstrated significant industry influence in AI. Hands-on experience with state-of-the-art LLMs. Preferred Qualifications Multiple first-author publications in LLM-related research at top-tier conferences. Expertise in deploying ML models and transitioning research to production. Experience with distributed ML frameworks ("e.g., Spark, Hadoop"). Familiarity with generative AI tools, LLMs, Transformers, reinforcement learning, or advanced NLP/Computer Vision techniques. Proven ability to influence business decisions through AI solutions. #J-18808-Ljbffr