3+ years of applied ML/AI experience, including hands-on work building LLM-powered or agentic applications. Strong programming skills in Python and experience with modern ML and deep learning frameworks (e.g., PyTorch). Hands-on experience with agentic frameworks, tool use, and data pipelines. Strong evaluation mindset: comfortable designing golden sets, metrics, and telemetry to drive iteration. Excellent communication and collaboration skills, with the ability to align with subject-matter experts and translate their domain knowledge into agent behavior. Hands-on experience with stateful, multi-turn agentic frameworks and complex execution flows. Experience with prompt engineering and optimization techniques. Experience with model adaptation (e.g., fine-tuning, distillation, preference optimization). Publications at top-tier venues (e.g., NeurIPS, ICML, ICLR, ACL, EMNLP, or similar). Familiarity with chip design or EDA environments. MSc, or PhD in Computer Science, Computer Engineering, Electrical Engineering, or related fields
