AI Engineer

Cinder•New York, NY

About The Position

Cinder provides a cutting-edge platform to protect the internet. Cinder safeguards the interaction layer: the front end of products that users engage — and sometimes abuse. Our AI agents, integrated workflow platform, and deep expertise power real-time integrity at the speed of innovation. We support some of the most important and innovative companies in the world, including OpenAI, Midjourney, and ElevenLabs. Cinder is backed by Accel and Y Combinator. We care deeply about being relentless, intentional, and empathetic. We hire gritty thinkers who set ego aside, aggressively solve customer problems, and get better every day. We’re building an enterprise-grade platform to make the internet safer and we need highly curious, hard-working self-starters. 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.

Requirements

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

Nice To Haves

Experience with agentic frameworks like langchain is a plus

Responsibilities

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.