About this role
Summary: Lead hands-on engineering and applied machine learning at an early-stage B2B SaaS company. Shape platform architecture, technical roadmap, and engineering standards while leading a small engineering pod and shipping critical work.
### About the Role
Lead hands-on engineering and applied machine learning at an early-stage B2B SaaS company. You will shape the platform architecture and technical roadmap with the founders while leading a small engineering pod.
### What You'll Do
- Build and lead a pod of engineers, supporting their growth, performance, and hiring while shipping critical work yourself.
- Own platform architecture and make build-versus-buy and infrastructure decisions.
- Set engineering standards, code review criteria, release practices, definitions of done, and on-call policies.
- Lead technical design and initial implementation of new initiatives.
- Assess applied machine learning research and determine what is suitable for production systems.
- Partner with the CTO on product direction, model strategy, and machine learning approaches.
### What We're Looking For
- Typically 5 to 8 years of engineering experience, with exceptional candidates considered from 4 to 5 years.
- Experience in an AI-native company, with technical leadership or ownership that helped build and support an engineering team.
- Hands-on experience training and deploying machine learning models in commercial production products, beyond integrating language model APIs.
- End-to-end ownership of technical architecture, infrastructure decisions, and engineering standards.
- Recent experience personally shipping production software, plus a record of stable engineering tenure.
- Strong applied machine learning judgment, including classical methods and current approaches to transformers and agent applications.
- Comfort with ambiguity, inherited code, hands-on development, and AI-assisted engineering workflows.
### Compensation & Benefits
Base salary: $200,000 to $400,000 annually. Visa sponsorship is not available.
### Location
On-site in New York, New York.