5-8 years of engineering experience, with flexibility for exceptional candidates with 4-5 years.
Experience in an AI-native company with technical leadership or ownership.
Hands-on experience in training and deploying machine learning models in production.
End-to-end ownership of technical architecture and engineering standards.
Recent experience in shipping production software with stable tenure.
Strong judgment in applied machine learning, including classical methods and modern approaches.
Comfortable with ambiguity and hands-on development.
Responsibilities
Build and lead a team of engineers, fostering their growth and performance.
Own platform architecture and make critical build-versus-buy decisions.
Establish engineering standards, code review criteria, and release practices.
Lead technical design and initial implementation of new initiatives.
Evaluate applied machine learning research for production suitability.
Collaborate with the CTO on product direction and machine learning strategies.
Benefits
Opportunity to shape platform architecture and technical roadmap.
Hands-on leadership role in a small engineering pod.
Direct collaboration with founders and CTO.
Focus on applied machine learning in a B2B SaaS environment.
Full Job Description
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
