Machine Learning Engineer - LLMs
HadrianAerospace & company
Los Angeles, United States$160,000 - $250,000Senior
Founders Fund
Lux Capital
Andreessen Horowitz
T. Rowe Price
Altimeter Capital
Morgan Stanley
Data & AI
About the role
TL;DR
Develop and deploy language models for manufacturing data analysis.
- •As a Senior Machine Learning Engineer, you will own the ML lifecycle for the language models that understand and reason about the content in manufacturing data packages.
- •Key Responsibilities Research, develop, and deploy fine-tuned language models for document classification, key information extraction, table parsing, and multi-page/document reasoning Work alongside the core engineering team to build and maintain annotation tooling, implement active learning loops, and engineer synthetic data augmentation strategies Develop evaluation frameworks that extend beyond accuracy and CER, precisely quantifying system behavior and user impact Collaborate with the other members of the machine learning team to set the technical and product roadmaps for the AI platform Burn down the long tail, as every percentage point of accuracy maps to man-years of time savings at our scale Requirements 5-8 years of professional AI/ML experience, with at least 2 years working directly with large language models (fine-tuning, RLHF/DPO, or pre-training), with special consideration for work with layout-aware models Strong Python and PyTorch fluency: You've written custom training loops, loss functions, and data loaders from scratch when needed Production deployment ownership: You've shipped models to production and have been responsible for endpoint and model health MS or PhD in Computer Science, Electrical Engineering, or related field preferred; equivalent industry experience valued equally
Required skills
PythonPyTorch
Domain expertise
aerospacedefense
Benefits & perks
Medical, dental, vision, and life insurance plans for employees, 401k, Relocation support may be provided for certain situations, based on business need., Flexible vacation policy, Equity
Tech stack
PythonPyTorch