Senior Applied Scientist(LLM)

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We are seeking a Senior Applied Scientist with strong hands-on experience in building and optimizing large language models (LLMs), agentic AI systems, and end-to-end model training workflows. This role is ideal for scientists with a solid applied background who can translate state-of-the-art research into real-world impact. A research-oriented mindset with publications in top AI/ML venues is highly preferred but not strictly required. You will collaborate closely with product, engineering, and research teams to ship intelligent, reliable, and innovative AI capabilities at scale.

• M.S. or Ph.D. in Computer Science, Machine Learning, or a related field, or equivalent practical experience.
• 4+ years of experience in applied machine learning, with a focus on LLMs, agent systems, or reinforcement learning.
• Strong hands-on experience with model training pipelines using PyTorch, TensorFlow, JAX, or similar frameworks.
• Familiarity with distributed training, prompt engineering, evaluation strategies, and model deployment best practices.
• Experience with retrieval-augmented generation (RAG), tool use, planning agents, or long-context modeling is a plus.
• Solid publication record (e.g., NeurIPS, ICLR, ACL, ICML, EMNLP) is a plus, but emphasis is placed on practical contributions.
• Strong coding and debugging skills, and comfort working in cross-functional, agile environments.

• Design and implement advanced LLM-based architectures and agentic systems for real-world product scenarios.
• Lead model training and evaluation efforts, including data preprocessing, fine-tuning, and inference optimization.
• Collaborate across teams to deliver robust, scalable models aligned with product objectives and user value.
• Apply and adapt research ideas to solve practical challenges in reasoning, planning, memory, and alignment.
• Monitor and improve model performance post-deployment through data-driven iteration and error analysis.
• Contribute to technical discussions, model reviews, and best practices within the applied science community.