5-8 years of engineering experience, with flexibility for exceptional candidates
Proven experience in training and deploying machine learning models in production
Demonstrated end-to-end ownership of technical architecture and infrastructure decisions
Experience in setting engineering standards and managing engineers while coding
Strong judgment in applied machine learning techniques, including classical methods and transformers
Recent hands-on experience shipping production software and navigating inherited code
Responsibilities
Build and lead a small engineering pod, focusing on team growth and performance
Own platform architecture and make impactful build-versus-buy decisions
Establish engineering standards for AI-assisted development processes
Lead technical designs and initial implementations for new projects
Evaluate applied ML research for production suitability
Collaborate with technical leadership to shape product roadmap and ML strategy
Balance hands-on coding with team leadership responsibilities
Benefits
Visa sponsorship is not available
On-site work in New York City
Full Job Description
About the Role
Lead engineering for an early-stage SaaS team building applied AI products for enterprise software. You will partner with the technical leadership team on architecture, product direction, and machine learning strategy while leading a small engineering pod and remaining hands-on with critical work. What You'll Do
Build and lead a pod of three to four engineers, supporting their growth, performance, and hiring while shipping key work yourself.
Own platform architecture and make build-versus-buy and infrastructure decisions with product and revenue impact.
Set engineering standards for AI-assisted development, including review criteria, definition of done, release cadence, and on-call practices.
Lead technical designs and initial implementations for new initiatives.
Evaluate applied ML research and determine which techniques are suitable for production systems.
Partner with technical leadership to shape the product roadmap, model strategy, and ML approach.
Initially spend most of your time building, with the balance focused on team leadership.
What We're Looking For
Typically 5 to 8 years of engineering experience, with 4 to 5 years considered for exceptional candidates.
Experience training and deploying machine learning models in production, beyond integrating LLM APIs.
End-to-end ownership of technical architecture, infrastructure decisions, and build-versus-buy tradeoffs.
Experience setting engineering standards and leading or managing engineers while continuing to code.
Strong applied ML judgment across classical methods and newer approaches, including transformers and agent applications.
Recent experience personally shipping production software, comfort with ambiguity and inherited code, and effective use of AI coding agents.
Compensation & Benefits
Annual salary range: $200,000 to $400,000 USD. Visa sponsorship is not available. Location
