Machine Learning Engineer – AI Infrastructure / Intelligent Agents
Location: New York City (100% in-office)
A fast-growing, AI-first startup in NYC is building intelligent agents designed to handle complex, high-trust workflows inside professional organizations. Their mission: to apply large language models in ways that actually scale, automate real tasks, and make professionals radically more effective—starting with one of the most foundational systems in the economy.
This team isn’t building chatbots. They're designing structured, agentic systems already running in production environments across major firms. With a recent Series A and rapidly increasing usage, they’re hiring a Machine Learning Engineer to help scale both the technology and the team.
What You’ll Do
- Architect and implement LLM-powered pipelines and intelligent agent frameworks
- Work on retrieval, reasoning, orchestration, and deployment at production scale
- Collaborate closely with founders and a small engineering team to ship fast and iterate
- Build mission-critical infrastructure in an industry undergoing rapid change
- Contribute on-site with the rest of the team in a collaborative NYC office
What They’re Looking For
- 4+ years experience in machine learning, ML infrastructure, or applied AI engineering
- Deep familiarity with LLMs, agent systems, and frameworks like RAG or ReAct
- Strong coding ability in Python and comfort owning end-to-end ML systems
- Thrives in startup environments: scrappy, thoughtful, fast-moving
- Willing and excited to work in-person in New York City, full-time
Bonus Points For
- Experience building production-grade agentic systems or decision-making engines
- Background in accounting, finance, or high-compliance enterprise domains
- Startup experience or history of navigating ambiguity and building from scratch
Why This Role
- Work on real-world agentic AI used in production by large firms
- Join early and influence the technical and cultural foundation of the company
- Build for depth, not hype—this is infrastructure, not a demo
- Strong compensation, meaningful equity, and a chance to be in the room where it happens
