Principal AI/ML Engineer, Deep Agentic Reasoning Engineer (Lorenz Labs) - CA, San Jose, Rio Robles, United States

Originally posted 11 September 2026 by the employer.

About the role

This role involves designing and building multimodal reasoning models for Edge AI applications.

What you'll do

• Develop and evaluate deep learning models for multimodal classification and reasoning tasks.
• Engage in the full research lifecycle, including data collection, annotation, preprocessing, model training, and evaluation.
• Prototype models in Python (using PyTorch/TensorFlow) and implement core reasoning improvements.
• Apply distillation techniques to transfer reasoning capabilities from larger models to smaller, efficient models.
• Document experiments and results through internal reports, blog posts, and publications.

What you'll need

• 10+ years of experience releasing software products with a strong track record of AI/ML success.
• 6+ years of experience releasing AI/ML products.
• PhD in AI-related fields such as NLP, Computer Vision, or Speech Processing.
• Strong publication record in NeurIPS, ICML, ICLR, ACL, NAACL, EMNLP, or CVPR.
• Proficiency in training, post-training, and evaluating transformer-based models with deep understanding of training dynamics, architecture modifications, and optimization techniques.
• Expertise in supervised fine-tuning, RL (e.g., GRPO), and advanced post-training techniques for reasoning models.
• Experience in implementing and modifying transformer architectures (encoder/decoder variants, attention mechanisms, positional encodings).
• Advanced knowledge of techniques including Chain-of-Thought (CoT) and agentic tree search methods.
• Experience with multi-agent orchestration, task decomposition, and static frameworks (e.g., LangGraph) and dynamic multi-agent harnesses.

Skills: multimodal reasoning models, Edge AI, deep learning models, transformer-based models, agentic systems