Deep Agentic Reasoning Engineer (Lorenz Labs)
Core
Design and build multimodal reasoning models (time-series, audio, video) for Edge AI applications to advance agentic systems and physical intelligence.
Role type
Senior IC deep learning researcher (multimodal reasoning)
Builds
Multimodal reasoning models and agentic systems for Edge AI
Domain
AI research, Edge AI, Physical Intelligence
Deliverable
production ML models
Required skills
transformer-based model development, supervised fine-tuning, post-training techniques, multimodal reasoning frameworks, Chain-of-Thought reasoning, reinforcement learning for reasoning, LLM evaluation, task orchestration
Preferred skills
knowledge distillation, Langchain/langgraph integration, GRPO
Technologies
Python, PyTorch, TensorFlow
Responsibilities
Develop and evaluate deep learning models for multimodal classification and reasoning; Engage in the full research lifecycle including data collection, annotation, preprocessing, training, and evaluation; Prototype models and implement core reasoning improvements; Apply distillation techniques to transfer capabilities to smaller models; Document experiments and results through reports and publications
Seniority
Senior, research-focused IC
