What We Need (Must Haves)

• Advanced Degree: Masters or PhD in Computer Science, AI, or related field (or equivalent top-tier research lab experience).

• Advanced LLM Internals: You understand the specific failure modes of modern architectures regarding long-context recall, reasoning drift, and hallucination triggers in complex logic. You don't just fine-tune; you know how to mathematically constrain model outputs to ensure high-fidelity results.

• Applied Research: 8+ years of experience, with a track record of taking complex ML research and deploying it into production environments.

• Beyond APIs: Proven expertise in architecting autonomous agentic systems that go beyond simple retrieval. You have designed multi-agent orchestrators involving planning, tool use (function calling), and self-correction loops to solve multi-step reasoning problems reliably.

• Engineering Excellence: Strong proficiency in Python. You write clean, modular, object-oriented code, not just "notebook scripts."

What You Will Do

• Architecture Design: Architect high-reliability inference systems that solve the "hallucination problem" inherent in Large Language Models. You will move beyond out-of-the-box solutions to build defensible, proprietary IP.

• Advanced NLP Strategy: Define the strategy for domain adaptation and long-context reasoning. You will perform first-principles analysis to select the right approach (RAG, Fine-Tuning, or novel methods) based on rigorous benchmarking.

• Evaluation & Verification: Design and build proprietary evaluation frameworks to rigorously measure the performance and safety of our models before they touch client code.

• Technical Standards: Mentor the engineering team on the mathematical underpinnings of Transformer architectures and current SOTA research.