1 day ago
San Francisco, CA, USAMid Level
Base Salary
$140k - $140k/yr
Responsibilities
- Design, train, and evaluate machine learning models for production use cases.
- Build end-to-end ML pipelines covering data preprocessing, model serving, and monitoring.
- Translate product and business requirements into machine learning solutions with product and engineering partners.
- Debug and improve production models using monitoring data and real-world feedback.
- Write maintainable code and contribute to ML infrastructure and tooling.
- Participate in code reviews and share knowledge with teammates.
Requirements
- A degree and at least 3 years of professional machine learning or software engineering experience, including building and deploying production ML systems.
- Strong understanding of model selection, evaluation metrics, feature engineering, and validation techniques.
- Proficiency in Python and hands-on experience with TensorFlow, PyTorch, or scikit-learn.
- Experience implementing production pipelines for data preprocessing, model serving, and monitoring.
- Experience maintaining ML systems at scale with AWS SageMaker, GCP Vertex AI, Kubernetes, or Docker.
- Experience with production A/B testing or experimentation frameworks.
- Experience working in fast-moving product environments and iterating on ML systems based on production feedback.
Benefits
- Base salary of $140,000 USD annually.
- On-site work in San Francisco, California, United States.