AI/ML Engineer – Build Scalable Machine Learning Systems

About the role

Cinder is building the command center that helps major internet platforms fight abuse with AI. As an AI/ML Engineer you will partner with existing AI Engineers, Data Scientists and Data Engineers to turn massive streams of decision data into production‑ready models that directly influence customer outcomes.

Key responsibilities

• Transform raw customer data into model‑ready features and select the optimal modeling approach (gradient‑boosted trees, fine‑tuned LLMs, or third‑party APIs).
• Own the end‑to‑end pipeline from data ingestion, training, and evaluation to real‑time inference.
• Improve classification pipelines, confidence cascading, and detection strategies while balancing cost, latency, and accuracy.
• Design and build Cinder’s internal model training, hosting, and inference platform.
• Collaborate with engineering, data science, and data engineering teams to shape data infrastructure, evaluation metrics, and monitoring.

Required profile

• 5–8+ years of machine‑learning engineering experience on small teams, with shipped production models (gradient boosting, tree‑based, classifiers, embeddings).
• Hands‑on experience taking messy, imbalanced classification problems from raw data to production traffic.
• Proven ability to build ML infrastructure from scratch, including training pipelines, serving stacks, and monitoring.
• Startup or mid‑size company background where pragmatic trade‑offs were required.

Required skills

• Python
• PyTorch
• scikit‑learn
• langchain
• XGBoost
• MLOps (CI/CD for ML, model versioning, experiment tracking, drift detection, production monitoring)
• Databricks (bonus)
• AWS
• Terraform (infrastructure‑as‑code)

What we offer

• Health, vision, and dental benefits plus a 401(k) plan with employer matching.
• Fully paid commuter benefits, stocked office, and paid lunch and dinner.
• Relocation assistance and a collaborative onsite environment with regular all‑company events.