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.

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.