Software Engineer

Mission.dev; United States; Remote; USD 160,000 - 200,000; Full time

Benefits offered by this job

Equity

Health insurance

Unlimited PTO

Learning budget

Job summary

Mission.dev is seeking a Senior Software Engineer with deep expertise in mathematical optimization, algorithm design, or optimization-focused machine learning to tackle real-world scheduling problems from a production engineering perspective.

You will design optimization models, build production software, and work across backend, API, and frontend to deliver scalable solutions for school timetabling challenges. Strong collaboration with CTO and cross-functional partners is essential.

Qualifications

• 4–10 years of professional software engineering experience.
• Deep expertise in mathematical optimization, machine learning, or algorithm design, with the ability to apply that expertise to real-world engineering problems.
• Hands-on experience building optimization or machine learning models and turning them into working production software.
• Experience with optimization solvers such as Gurobi or OR-Tools CP-SAT, or a strong mathematical optimization background and the ability to learn new solvers quickly.
• Strong backend engineering skills and a willingness to remain hands-on with code for at least 50% of your time.
• Experience with Python or another relevant programming language, with Python strongly preferred.
• A degree in Computer Science or another related technical field.
• Strong problem-solving, communication, and project leadership skills.
• Availability to overlap with teammates in Europe and India during early morning hours in the US.

Responsibilities

• Design and implement optimization algorithms that generate high-quality school schedules under complex real-world constraints.
• Translate mathematical optimization problems into working models and production-ready software.
• Develop, test, and deploy linear optimization or machine learning models, depending on your area of expertise.
• Build and maintain backend services, APIs, background jobs, and AWS infrastructure supporting the optimization engine.
• Contribute to frontend development to help users understand and interact with scheduling results.
• Lead complex technical projects and work closely with the CTO, engineering team, and non-technical stakeholders.

Skills

4–10 years experience

Optimization/ML/Algorithms

Production software

Gurobi OR-Tools

Python

Backend engineering

Communication/leadership

Europe/India overlap

Education

B.S. in Computer Science or related field

Tools

Gurobi

OR-Tools CP-SAT

AWS

Job description

Remote – US-based | $160,000–$200,000 + Equity

About the Role

We're looking for a Senior Software Engineer with strong expertise in mathematical optimization, algorithm design, or optimization-focused machine learning to help solve complex real-world scheduling problems.

Our client is a fast-growing, venture-backed education technology company helping school districts build better school timetables through advanced optimization software. With a strong track record of customer renewals and a collaborative team, the company is investing in technology that makes complex scheduling more efficient and effective.

In this role, you'll turn complex constraints into mathematical models, develop optimization algorithms, and ship them as reliable production software. You'll work closely with a small engineering team and collaborate with technical and non-technical stakeholders to solve challenging problems at scale.

This is a hands-on software engineering role requiring both optimization expertise and production development experience. It is not a general ML, data science, or backend engineering position.

What You'll Do

• Design and implement optimization algorithms that generate high-quality school schedules under complex real-world constraints.
• Translate mathematical optimization problems into working models and production-ready software.
• Develop, test, and deploy linear optimization or machine learning models, depending on your area of expertise.
• Build and maintain backend services, APIs, background jobs, and AWS infrastructure supporting the optimization engine.
• Contribute to frontend development to help users understand and interact with scheduling results.
• Lead complex technical projects and work closely with the CTO, engineering team, and non-technical stakeholders.

Required Qualifications

• 4–10 years of professional software engineering experience.
• Deep expertise in mathematical optimization, machine learning, or algorithm design, with the ability to apply that expertise to real-world engineering problems.
• Hands-on experience building optimization or machine learning models and turning them into working production software.
• Experience with optimization solvers such as Gurobi or OR-Tools CP-SAT, or a strong mathematical optimization background and the ability to learn new solvers quickly.
• Strong backend engineering skills and a willingness to remain hands-on with code for at least 50% of your time.
• Experience with Python or another relevant programming language, with Python strongly preferred.
• A degree in Computer Science or another related technical field.
• Strong problem-solving, communication, and project leadership skills.
• Availability to overlap with teammates in Europe and India during early morning hours in the US.

Nice to Have

• Experience solving optimization problems in logistics, transportation, e-commerce, ride-hailing, or other constraint-heavy domains.
• Familiarity with AWS infrastructure.
• Additional background in machine learning, mathematics, electrical engineering, or a related quantitative discipline.
• Flexible cash/equity compensation mix.
• Health, dental, vision, and life insurance.
• Unlimited PTO.
• Learning and professional development budget.

Location & Work Authorization

• Fully remote within the United States.

Interested?

If you enjoy turning complex mathematical problems into practical software solutions and have experience deploying optimization models in production, we'd like to hear from you.