Principal AI/ML Engineer, Deep Agentic Reasoning Engineer (Lorenz Labs)
Core
Design and build multimodal reasoning models (time-series, audio, video, sensor data) for Edge AI applications and advance agentic systems.
Role type
Principal AI/ML Engineer (Deep Agentic Reasoning)
Builds
Multimodal reasoning models and agentic systems for the Intelligent Edge
Domain
Semiconductor, Edge AI, AI Research
Deliverable
production ML models
Required skills
Transformer model training and evaluation, Supervised fine-tuning, Reinforcement Learning (RL), Transformer architecture modification, Chain-of-Thought (CoT), Multi-agent orchestration, Knowledge distillation, Model deployment
Preferred skills
JEPA training, World models, Diffusion-based generation, Dynamic multi-agent harnesses
Technologies
Python, PyTorch, TensorFlow, LangGraph
Responsibilities
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 rigorous evaluation; Prototype models and implement core reasoning improvements; Apply distillation techniques to transfer reasoning capabilities; Document experiments and results through reports and publications
Seniority
Principal, hands-on IC with strategy & mentorship
