5-8 years of engineering experience, with flexibility for exceptional candidates with 4-5 years.
Proven experience in training and deploying machine learning models in production environments.
Strong background in technical architecture ownership, including infrastructure decisions.
Demonstrated ability to set and enforce engineering practices as a technical or people lead.
Recent hands-on experience in shipping software end-to-end with strong coding skills.
Applied machine learning expertise across classical and modern techniques, including effective use of AI coding agents.
Ability to navigate ambiguity and practical delivery challenges.
Responsibilities
Lead a small engineering team, fostering growth and performance while being hands-on with projects.
Own and make decisions regarding core platform architecture and infrastructure.
Establish engineering standards, including code review criteria and release practices.
Drive technical design and initial implementation for new initiatives.
Evaluate and select applied machine learning techniques suitable for production.
Collaborate with technical leadership on product direction and engineering roadmap.
Benefits
Equity participation in the company.
Opportunity to shape the technical foundation of a growing B2B SaaS team.
Hands-on leadership role with direct impact on product development.
Work in a dynamic, early-stage startup environment.
Full Job Description
About the Role
Join an early-stage B2B SaaS team as its hands-on engineering lead, shaping platform architecture and applied machine learning strategy alongside the technical founders. You will lead a small engineering pod while building and shipping critical product work, helping establish the technical foundation and practices for the team. What You'll Do
Lead a pod of three to four engineers, supporting their growth, performance, and hiring while remaining hands-on with key projects.
Own core platform architecture, infrastructure decisions, build-versus-buy choices, and cost considerations.
Set engineering standards, code review criteria, release practices, definitions of done, and on-call policies.
Lead technical design and initial implementation for new initiatives.
Evaluate applied machine learning approaches and distinguish techniques ready for production from those that are still speculative.
Partner with the technical leadership team on product direction, model strategy, and the engineering roadmap.
What We're Looking For
Typically 5 to 8 years of engineering experience, with exceptional candidates who have 4 to 5 years also considered.
Experience training and deploying machine learning models in production, beyond integrating third-party LLM APIs.
End-to-end ownership of technical architecture, including infrastructure and build-versus-buy decisions.
Experience setting engineering practices and holding a team accountable as a technical or people lead.
Recent experience personally shipping software end-to-end, along with strong hands-on coding skills.
Applied ML judgment across classical methods and newer approaches, plus experience using AI coding agents effectively.
Comfort working through ambiguity, existing code, and practical delivery challenges.
Compensation & Benefits
Base salary is $200,000 to $400,000 annually, with equity. Visa sponsorship is not available. Location
