Senior ML Engineer — Production-Grade ML Systems

Cinder; New York (NY); On-site; USD 170,000 - 230,000; Full time

Benefits offered by this job

Health benefits

Vision benefits

Dental benefits

401(k)

Commuter benefits

Office lunch and dinner

Job summary

Cinder is seeking an experienced AI Engineer to build scalable ML systems that turn customer data into production models shaping outcomes.

You’ll own data-to-decision pipelines, balance latency and accuracy, and collaborate with our AI, Data Science, and Engineering teams to deploy reliable ML infrastructure.

Relocation to NYC is available and we support a collaborative, fast-moving startup environment.

Qualifications

• 5–8+ years of ML engineering on a small team shipping ML systems to production.
• Experience taking models from messy data to production load-bearing systems.
• Understanding when to use LLMs vs classic models based on cost/latency tradeoffs.
• Hands-on experience building classifiers under severe class imbalance and production pipelines and monitoring.

Responsibilities

• Turn real-world customer data into learnable inputs and choose model approach (classical classifier, fine-tuned LLM, or bootstrap via API).
• Improve classification pipelines, confidence cascading, and detection strategies for efficient harm content detection.
• Develop features to aid moderators and reveal patterns across data.
• Partner with Engineering to build in-house model training, hosting, and inference platform.
• Design evaluation/metrics infrastructure for classifier scores, outputs, and iterations.
• Collaborate with Founding Data Scientist and AI Engineers on agent evaluation architecture.
• Work with Data Engineer to ensure data infrastructure supports training and production inference at required latency and scale.
• Mentor teammates and raise the ML bar across the company.

Skills

Python

PyTorch

scikit-learn

XGBoost

MLOps

LLMs

AWS

Terraform

Tools

Databricks

Langchain

Job description

Cinder is seeking an experienced AI Engineer to build scalable ML systems that turn customer data into production models shaping outcomes.

You’ll own data-to-decision pipelines, balance latency and accuracy, and collaborate with our AI, Data Science, and Engineering teams to deploy reliable ML infrastructure.

Relocation to NYC is available and we support a collaborative, fast-moving startup environment.