AI/ML Engineer

About this role

Cinder seeks an ML Engineer to build production-grade machine learning systems for content moderation at scale. You'll own the complete pipeline from messy real-world data to deployed models, balancing classical approaches with LLMs, while partnering with a small AI-focused team to shape the company's ML infrastructure.

What you'll do

• Build end-to-end ML pipelines from data cleaning through production model deployment, choosing appropriate model architectures based on latency, cost, and accuracy tradeoffs
• Improve content classification systems, confidence cascading, and detection strategies to efficiently catch harmful content while managing computational costs
• Develop features and evaluation infrastructure that support both ML models and AI agents, ensuring robust measurement of system performance
• Partner with engineering to design Cinder's in-house model training, hosting, and inference platform
• Build data pipelines and feature infrastructure with the data engineering team to support model training and production inference at scale
• Mentor teammates and establish ML best practices as the company scales its AI capabilities

What they're looking for

• Production machine learning systems (gradient boosting, tree-based models, classifiers)
• Classification under severe class imbalance and handling imbalanced datasets
• Python and ML frameworks (PyTorch, scikit-learn, XGBoost, LangChain)
• Feature engineering and train/test split strategy
• MLOps fundamentals including CI/CD, model versioning, and monitoring
• LLM evaluation and integration decisions
• Statistical metrics selection (precision, recall, F1, AUC)
• Building ML infrastructure and serving systems from scratch