Palo Alto, CA & Seoul, South Korea at Gauss Labs
Core
Building industrial AI foundation models and Transformer architectures for time-series forecasting on noisy, sparse, irregularly sampled sensor data to impact real production yield.
Role type
Senior IC machine-learning engineer (ML infrastructure) / AI scientist (ML research)
Builds
Tabular foundation models and Transformer architectures for manufacturing time-series forecasting
Domain
Industrial AI / Manufacturing / Time-series forecasting
Deliverable
production ML models
Required skills
Python, PyTorch, Docker, Kubernetes, CI/CD, distributed multi-GPU training, time-series modeling, Transformer architecture design, EDA, patent writing
Preferred skills
Experience with noisy/sparse sensor data, pretraining and fine-tuning at scale
Technologies
PyTorch, Docker, Kubernetes, CI/CD
Responsibilities
Own training/serving/monitoring infrastructure for foundation models; take models from prototype to production; design Transformer-based sequence models; conduct end-to-end EDA through deployment; publish and patent research
Seniority
Senior, hands-on IC / Senior, research & mentorship