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.