AI/ML Engineer

The role

You will build ML systems that turn customer decision data into production models. You will own the full path from data to decision, including model approach, classification pipelines, and evaluation infrastructure.

What you will do

• Turn real-world customer data into model-ready data and decide on model approaches.
• Improve classification pipeline, confidence cascading, and detection strategies.
• Develop intelligent features to help moderators and reveal data patterns.
• Partner with Engineering to build in-house model training, hosting, and inference platforms.
• Design and build evaluation and metrics infrastructure.
• Partner with the Founding Data Scientist and AI Engineers to shape agent evaluation architecture.
• Partner with the Data Engineer to shape data infrastructure for ML systems.
• Mentor teammates and raise the ML bar across the company.

Required qualifications

• 5–8+ years of machine learning engineering experience on a small team.
• Track record of shipping ML systems (gradient boosting, tree-based models, classifiers, embedding-based methods) to production.
• Experience taking classification problems from messy, unlabeled, real-world data to production traffic.
• Understanding of LLMs to make calls regarding cost and latency versus classic models.
• Hands-on experience building classifiers under severe class imbalance.
• Experience standing up training pipelines, serving infrastructure, evaluation harnesses, and monitoring from scratch.
• Startup or small/mid-size company experience with meaningful scope and pragmatic tradeoffs.
• Fluency with feature engineering, leak-aware train/test splits, metric selection on imbalanced data, cross-validation, and hyperparameter tuning.
• Strong Python skills.
• Hands-on experience with AI & ML frameworks (PyTorch, scikit-learn, langchain, XGBoost etc).
• Solid MLOps foundation including CI/CD for ML, model versioning, experiment tracking, drift detection, and production monitoring.
• Experience designing inference systems with explicit latency and throughput targets.

Nice to have

• Experience with training, evaluating and serving models via Databricks
• Experience with AWS and infrastructure-as-code (Terraform)

Benefits

• Health, vision & dental benefits
• 401(k) plan with employer matching
• Fully paid commuter benefits
• Fully stocked office with paid lunch and dinner

Before you apply

• Cinder will relocate for this role

About the company

Cinder is mission-critical infrastructure that provides a command center for large internet platforms to fight fraud, abuse, and manipulation. They are a small, fast-moving team backed by Accel and Y Combinator.