Lead strategy, architecture, and implementation of ML systems for internal/external apps.
Own the full model lifecycle: feature engineering, training, and serving.
Build robust MLOps infrastructure with monitoring, testing, CI/CD.
Architect cloud-native ML infrastructure on GCP.
Operate in an internal-startup mode with high visibility.
In-office presence 2-3 days/week in San Francisco, CA.

🎯 Requirements

2+ years of professional experience as a Machine Learning Engineer or similar role.
Strong mathematical intuition and problem-solving skills.
Python and NumPy/scikit-learn ecosystem expertise.
Experience with PyTorch, TensorFlow, or JAX.
Production ML deployment with Kubeflow, MLflow, Airflow, or TFX.
Docker/Kubernetes for ML serving; familiarity with GCP.

🎁 Benefits

Salary range: $362,000 - $422,000 USD.
Eligible for carry program and discretionary bonuses.
Health, dental, vision, disability, life, 401K, vacation, sick leave.

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