AI Engineer

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.

Cinder is seeking an AI/ML engineer to architect and deploy production AI systems at scale. You'll contribute to the strategic vision for machine learning and AI at Cinder, collaborating with data and software engineers to build world-class AI capabilities that directly impact our product and business outcomes.

We're looking for an engineer first - someone who builds, ships, and maintains production systems rather than writing papers. If you've taken ML models from experimentation to production at scale, navigated the messy realities of real-world data, and understand that robust infrastructure matters as much as model performance, we want to talk.

• Own the complete lifecycle of large language model implementation: from data preparation and fine-tuning through rigorous evaluation and production deployment.

• Develop automated evaluation frameworks that continuously assess model accuracy, identify edge cases, and quantify improvements across iterations.

• Work directly with product managers and engineers to integrate AI as a core product capability.

• Shape our AI roadmap by staying current with industry developments, evaluating emerging techniques, and making pragmatic adoption decisions.

• Design and implement low-latency, high-throughput, cloud-based AI/ML systems capable of handling thousands of requests per second

• Build the foundational infrastructure - model serving, monitoring, deployment pipelines, and automated testing frameworks - that enables rapid experimentation and iteration while maintaining production reliability.

• 5-7+ years of engineering experience with demonstrated hands-on knowledge of applying LLMs and agents in industry

• Experience at a high-growth startup building machine learning infrastructure from the ground up

• Demonstrated ability to take models from research/experimentation through production deployment at scale

• Fluency in Python and related AI/ML frameworks (TensorFlow, PyTorch, Keras, etc.)

• Hands-on experience with LLMs and contemporary AI engineering patterns: RAG architectures, embedding models, vector databases, prompt engineering, and fine-tuning strategies

• Curious, systematic, and execution-oriented—you don't wait for perfect requirements and can navigate technical tradeoffs independently

• Strong foundation in MLOps: CI/CD for ML, model versioning, monitoring, and observability

• Strong technical background in AWS cloud architecture and automated infrastructure provisioning with Terraform

• Experience with agentic frameworks like langchain is a plus

We're based in NYC and would relocate the right person 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.