---
title: 'AI/ML Engineer at Cinder'
canonical: 'https://feeny.ai/job/ai-ml-engineer-cinder-new-york-v5cccq6293na'
type: 'job'
last_seen: '2026-09-06'
---

# AI/ML Engineer at Cinder

- **Company:** Cinder
- **Location:** New York, NY
- **Employment:** full-time
- **Work type:** hybrid
- **Posted:** 2026-08-27
- **Last confirmed live:** 2026-09-06
- **Apply:** https://jobs.ashbyhq.com/cinder/683bb5d5-c354-4fa6-ba1f-1d54c59a470b

## Job description

## ABOUT CINDER

Cinder is the mission-critical infrastructure that keeps the world's most important digital platforms true to what they stand for. The internet has always been abused by bad actors, and AI is making it exponentially worse, driving fraud, abuse, and manipulation at a scale and speed no human team can fight alone. Cinder gives platforms one command center to fight back: to write and enforce policy, deploy AI agents against abuse in real time, investigate threats, file NCMEC reports, and prove their safety programs are working.

Our customers are some of the largest internet platforms in the world. The decisions made in our software directly determine what stays up, what comes down, and how users are treated.

We're a small, fast-moving team backed by Accel and Y Combinator. We care about being intentional, direct, and deeply focused on solving real customer problems.

## WHY THIS ROLE

Cinder is expanding quickly, and we want to bring on an additional AI Engineer to partner with our current AI Engineers, Data Scientist, and Data Engineer. You'll build the ML systems that make Cinder faster, more efficient, and more accurate, turning the enormous volume of customer decision data we process into production models that directly shape customer outcomes.

We're looking for a builder. Someone who has taken models from messy data to production at scale, who reaches for a gradient-boosted tree before a transformer when that's the right call, and who has stood up ML infrastructure from scratch rather than inheriting it fully-built. What matters most is judgment: knowing the smallest, most efficient, most reliable model for the job, and understanding both ML methods and LLMs deeply enough to make that call yourself rather than defaulting to whichever one you know best. This role needs someone who cares as much about precision-recall tradeoffs, class imbalance, and serving latency as they do about model architecture.

## WHAT YOU'LL DO

- Turn real-world customer data into something a model can actually learn from, then decide what model approach fits: a classical classifier when it wins on cost and latency, a fine-tuned LLM when the tradeoff is worth it, a third-party API as a bootstrap. You own the full path from data to decision, not just the model.
- Improve our classification pipeline, confidence cascading, and detection strategies so we catch harmful content efficiently — balancing cost, latency, and accuracy deliberately.
- Develop intelligent features that help moderators make decisions, organize platform content, and reveal patterns across our data.
- Partner with Engineering to build out Cinder's in-house model training, hosting, and inference platform.
- Design and build the evaluation and metrics infrastructure customers rely on, including how classifier scores and model outputs are calculated, stored, surfaced, and iterated on.
- Partner with our Founding Data Scientist and AI Engineers to shape the agent evaluation architecture — measuring whether our agent fleet is making the right decisions with the right tools at the right cost.
- Partner with our Data Engineer to shape the data infrastructure powering our ML systems, ensuring model training, feature pipelines, and production inference have the right data flowing at the right latency and scale.
- Mentor teammates and raise the ML bar across the company as Cinder's ML capability matures.

## WHAT WE’RE LOOKING FOR

- 5–8+ years of machine learning engineering experience on a small team, with a strong track record of shipping ML systems (gradient boosting, tree-based models, classifiers, embedding-based methods) to production.
- You've taken a classification problem from messy, unlabeled, real-world data all the way to a model that shipped and served production traffic.
- You understand LLMs well enough to make an informed, defensible call about when an LLM is worth its cost and latency versus a classic model.
- Real, hands-on experience building classifiers under severe class imbalance, where the signal you care about is a small minority of the data
- Thrived in environments where the ML infrastructure wasn't already built for you: you've stood up training pipelines, serving infrastructure, evaluation harnesses, and monitoring from scratch rather than inheriting a mature platform.
- Startup or small/mid-size company experience where you owned meaningful scope and had to make pragmatic tradeoffs about what to build, what to buy, and what to defer.
- Deep fluency with the fundamentals: thoughtful feature engineering, leak-aware train/test splits, metric selection on imbalanced data (precision/recall/F1/AUC over accuracy), cross-validation, and principled hyperparameter tuning.
- Strong Python skills and hands-on experience with AI & ML frame works: (PyTorch, scikit-learn, langchain, XGBoost etc)
- Solid MLOps foundation: CI/CD for ML, model versioning, experiment tracking, drift detection, and production monitoring. Bonus if you have experience with training, evaluating and serving models via Databricks
- Experience designing inference systems with explicit latency and throughput targets, and independently making informed tradeoffs between model complexity, cost, and performance.
- Experience with AWS and infrastructure-as-code (Terraform) is a plus.

## LOCATION & BENEFITS

We're based in NYC and will relocate for this role. We believe in working together in person and hold at least two all-company events per year. We offer health, vision & dental benefits, a 401(k) plan with employer matching, fully paid commuter benefits, and a fully stocked office with paid lunch and dinner.

## About Cinder

## Company Overview
- **One-liner**: Cinder provides mission-critical trust and safety infrastructure that protects online platforms from AI-powered abuse, fraud, and manipulation.
- **Entity Type**: Private (Series B)
- **Headquarters**: New York City, USA
- **Founded**: 2022
- **Founders**: Glen Wise and Phil Brennan

## Core Business
- **Primary industry**: Trust and Safety, AI Infrastructure, Cybersecurity
- **Target customers**: B2B; platforms of all sizes from startups to enterprises, including frontier AI labs, e-commerce, and social media companies
- **Mission or purpose**: To protect the internet from AI-powered abuse by building infrastructure that outmatches the speed and scale of AI-empowered bad actors.

## Products & Services
- **Cinder Platform**: A single command center for every safety workflow and tool. It centralizes policies, data consolidation, and AI-backed automations to improve alignment and efficiency. Features include real-time detection, context-aware decisions, AI red teaming, quality assurance, and explainability/audit trails.
- **Custom AI Agents**: Configurable agents that enforce standards and policies across millions of decisions, adapting to specific policies and learning continuously from mistakes and successes. They can examine images, conversations, full user profiles, and networks of related entities.
- **Managed Operations**: Expert services for content moderation, case investigation, IP and copyright enforcement, user fraud and account takeover detection, and custom agent development.
- **Data Labeling**: Accurate, AI-ready training data with real-time evaluation and faster turnaround.
- **Applicant Fraud Detection**: Vetting candidates for sensitive roles using the same intelligence applied to abuse detection, integrated directly into an ATS.

## Market Standing
- **Valuation/Market Cap**: Not publicly disclosed
- **Key Metric**: Raised $41M in Series B funding (announced in 2024)
- **Notable Investors/Partners**: Y Combinator (Winter 2022 batch), with Brad Flora as primary partner. Integrates with IWF, Salesforce, StopNCII, and others.
- **Growth Signals**: Processes 400M+ events daily, protects 3B+ end-users, automates 94% of human review, saves 100k+ hours, and achieves >97% AI moderation accuracy. The company is scaling rapidly to combat the surge in AI-generated abuse.

## Competitive Advantages
- **Agentic AI Infrastructure**: Unlike off-the-shelf classifiers, Cinder’s AI agents adapt to specific policies, learn continuously from mistakes and successes, and can examine complex analytical units (images, conversations, full user profiles, networks of related entities).
- **Founder Expertise**: Founders spent years countering terrorism, child exploitation, and nation-state actors at Meta and in government, giving them deep domain expertise.
- **System of Record**: Centralizes policies, review teams, enforcement paths, vendors, and AI systems in one operational surface, with full audit trails and compliance documentation.
- **Enterprise-Grade Security**: SOC2, GDPR, and HIPAA compliant, with role-based permissions, SSO, and encrypted data.

## Products & Services
- **Cinder Platform**: A single command center for every safety workflow and tool. Features include real-time detection, quality assurance, access management, and AI-powered workflow builders. Acts as a system of record for all safety operations.
- **Custom AI Agents**: Configurable agents that enforce standards and policies across millions of decisions. They adapt to specific policies, learn continuously, and can examine complex analytical units (images, conversations, full user profiles, networks).
- **Managed Operations**: Expert services for content moderation, case investigation, IP and copyright enforcement, user fraud and account takeover detection, and custom agent development.
- **Data Labeling**: Accurate, AI-ready training data with real-time evaluation and faster turnaround.
- **Applicant Fraud Detection**: Vetting candidates for sensitive roles using the same intelligence applied to abuse detection, integrated directly into an ATS.

## Market Standing
- **Valuation/Market Cap**: Not publicly disclosed
- **Key Metric**: Raised $41M in Series B funding (announced in 2024)
- **Notable Investors/Partners**: Y Combinator (Winter 2022 batch, primary partner Brad Flora). Integrates with IWF, Salesforce, StopNCII, and others.
- **Growth Signals**: Processes 400M+ events daily, protects 3B+ end-users, automates 94% of human review, saves 100k+ hours, and achieves >97% AI moderation accuracy. The company is scaling rapidly to combat the surge in AI-generated abuse.

## Competitive Advantages
- **Founder Expertise**: Founders spent years countering terrorism, child exploitation, and nation-state actors at Meta and in government, giving them deep domain knowledge and credibility.
- **Agentic AI Infrastructure**: Unlike off-the-shelf classifiers, Cinder’s AI agents adapt to specific policies, learn continuously from mistakes and successes, and can examine complex analytical units (images, conversations, full user profiles, networks).
- **System of Record**: Centralizes policies, review teams, enforcement paths, vendors, and AI systems in one operational surface with full audit trails and compliance documentation.
- **Enterprise-Grade Security**: SOC2, GDPR, and HIPAA compliant, with role-based permissions, SSO, and encrypted data.

## Strategic Focus
- **Scaling AI Agent Capabilities**: Continuously improving AI agents to outmatch the speed and scale of AI-empowered bad actors.
- **Expanding Platform Integration**: Connecting existing models and third-party tools (IWF, Salesforce, StopNCII) to create a unified safety ecosystem.
- **Hiring in NYC**: Focused on building a strong in-person team in New York City, with team members also across the US and UK/EU.

## Why Work Here
- **Mission-Driven Work**: Employees tackle urgent, high-stakes problems like deepfake nudes, child sexual abuse material, AI-generated phishing campaigns, and organized crime. The work is described as "urgent, visible, and high-stakes."
- **Fast-Paced Culture**: The company ships in days, not quarters, and makes decisions with incomplete information. Speed is not optional because adversaries are moving fast with AI.
- **Values**: "Own the Outcome," "Ship Relentlessly," "Mission Over Ego," and "Customer Obsessed." The team is deliberate about building a diverse group with different backgrounds and perspectives.
- **Work Policy**: Hybrid; based in New York City with team members across the US and UK/EU. The company holds at least two all-company gatherings per year and is especially focused on hiring in NYC, with relocation support for the right candidates.
- **Benefits**: Competitive health, vision, and dental coverage; 401(k) with employer matching; paid family leave; flexible paid time off; fully paid commuter benefits; and a fully stocked NYC office with paid lunch and dinner.

## Sources
1. [cinder.ai](https://cinder.ai)
2. [cinder.ai/careers](https://cinder.ai/careers)
3. [cinder.ai/about](https://cinder.ai/about)
4. [jobs.ashbyhq.com/cinder](https://jobs.ashbyhq.com/cinder)
5. [ycombinator.com/companies/cinder-2](https://www.ycombinator.com/companies/cinder-2)

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