The role
- COMP
- $160K - $200K
- EQUITY
- Competitive equity
- LOCATION
- New York · Boston
- WORKPLACE
- Remote
- EXPERIENCE
- 4 - 10 years
- VISA
- None, Visa transfers
- STACK
- Python, AWS, Terraform, CI/CD
- INDUSTRY
- Education, Edtech, AI
/roles — ROLE_219
Senior Software Engineer, Optimizer (Remote)
Growing edtech company using optimization and AI to help school districts build their master schedules
The company
Education technology company pairing AI optimization with hands-on expert support so school districts can build better master schedules for their teachers and students.
- STAGE
- Series A-stage
- FUNDING
- $7M raised
- TEAM
- ~60 people
- FOUNDED
- 2023
JD — the work
About the role
The optimizer team builds the core engine that schedules students and teachers for schools serving hundreds of thousands of students across many states. The work blends full-stack engineering with ML and mathematical optimization, tackling a notoriously tough combinatorial puzzle for schools. You would join a small, strong team whose lead is a senior engineer from big tech with a math PhD, with room to grow into a tech lead.
What you'll do
- Grow the central MIP/LP scheduling model, plus the services and infrastructure it runs on
- Try ML and AI methods that make schedules more accurate, faster to produce, and easier for users
- Work across the stack, about 80% backend and 20% frontend, so users can drive the optimizer more directly
- Take full ownership of critical systems: on-call shifts, debugging customer problems, and partnering with school-facing success staff
- Drive complicated technical efforts and grow into the tech lead role over time
What they're looking for
- 4+ years building software, with a history of leading hard technical initiatives rather than only completing assigned tasks
- Strength in one of: mathematical optimization, production ML, or backend APIs and infrastructure, plus eagerness to pick up the rest
- Ownership of a core algorithm, model, or optimizer behind a key product feature, not just logging or data pipelines
- Comfort with on-call and with getting yourself unstuck anywhere in the stack (Python, AWS, Terraform, frontend)
- Clear communication with non-technical colleagues and real curiosity about the education domain, beyond the code itself