Machine Learning Engineer - Agentic AI ($250,000)

AttisSan Francisco Bay Area
Full TimeOn-siteMid$100,000 - $250,000 / YearLimited info disclosed
41 views0 applications

Description

Machine Learning Engineer AI Simulation / Agentic Systems Deep Tech Startup (Aerospace & Defense AI) $100,000 – $250,000 + Equity The Company • Early-stage company building AI-driven engineering simulation platforms • Products across CFD, FEA, and flight control systems • Supporting aerospace, automotive, and defense sectors • Focused on automating complex engineering workflows using AI Why Join? • Build cutting-edge agentic AI for real-world engineering problems • High ownership in an early-stage, zero-bureaucracy environment • Work directly with founders on product direction • Solve technically complex problems at intersection of AI + physics • Opportunity to shape production systems used by major industries The Role A technical, hands-on role where you will: • Design and deploy LLM-based multi-agent systems • Build coding agents for simulation and engineering workflows • Implement RAG, reinforcement fine-tuning, and evaluation pipelines • Train deep learning models from scratch using PyTorch • Integrate AI systems with external engineering tools • Develop human-in-the-loop workflows for AI systems • Continuously improve model architectures and agent performance The Essential Requirements • 3+ years ML engineering / AI systems experience • Production LLM system architecture experience • Strong ML fundamentals and model training experience • Proficiency in PyTorch and transformer architectures What Will Make You Stand Out • Experience with coding agents or developer tooling • Reinforcement learning / RFT experience • Background in scientific computing or simulations If you are interested in this role, please apply with your resume through this site. Keywords for Search (SEO) Machine Learning Engineer, AI Engineer, LLM Engineer, Agent Systems, PyTorch, Transformers, RAG, RLHF, Reinforcement Learning, Deep Learning, AI Simulation, Multi Agent Systems, Python, Distributed Training Show more Show less