Optimization Engineer- Routing Systems

• Model & Algorithm Development: Design, build, and implement advanced optimization models for various VRP contexts, including Capacitated VRP (CVRP), VRP with Time Windows (VRPTW), and dynamic routing scenarios. 
• Heuristics & Solvers: Develop and refine custom heuristics and metaheuristics (e.g., Tabu Search, Genetic Algorithms) to find high-quality solutions for large-scale, real-world problems. Utilize commercial and open-source solvers (e.g., Gurobi, CPLEX, Google OR-Tools). 
• Data Analysis & Simulation: Analyze historical and real-time data—including student locations, school bell times, traffic patterns, and vehicle telematics—to inform model parameters and constraints. Build simulation frameworks to test and validate model performance before deployment. 
• Predictive Modeling: Build and deploy machine learning models to support the routing engine, focusing on areas like travel time estimation (ETAs), demand forecasting, and anomaly detection. 
• Cloud-based Data Science - Standing up and working in cloud-based data science environments. 
• MLOps & Model Lifecycle Management: Own the end-to-end lifecycle of predictive models, including automated deployment, performance monitoring, drift detection, and continuous retraining to ensure accuracy and reliability in a live production environment. 
• Production Implementation: Write robust, production-ready Python code to integrate your optimization and ML models into our live operational platform. Work closely with software engineers to expose your models via APIs. 
• Performance Measurement: Define and monitor key performance indicators (KPIs) such as on-time performance, ride duration, vehicle utilization, and cost-per-student. Continuously iterate on models to drive improvements. 
• Strategic Collaboration: Partner with product, operations, and engineering teams to understand business constraints and translate them into mathematical models. Clearly communicate complex findings and recommendations to both technical and non-technical stakeholders. 

• Master’s degree or PhD in Operations Research, Industrial Engineering, Computer Science, Applied Mathematics, or a related quantitative field. (A Bachelor's degree with exceptional relevant experience will be considered). 
• 3+ years of professional experience in an operations research, data science, or quantitative role with a focus on optimization or machine learning. 
• Deep theoretical and practical understanding of the Vehicle Routing Problem and its variants, and solution methodologies. 
• Strong background in mathematical optimization, linear programming, statistical analysis, and combinatorial optimization 
• Proven experience building and implementing optimization or ML models in Python (or R with experience translating R to production-level Python code) 
• Experience with open source data science toolkits including Python (numpy, pandas, scikit, PySpark) or R (Tidyverse/Tidymodels) 
• Hands-on experience with at least one optimization solver (e.g., Gurobi, CPLEX, SCIP, Google OR-Tools). 
• Familiarity with geospatial data and tools (e.g., PostGIS, GeoPandas, OSRM).  
• Proficiency with data science and machine learning libraries (e.g., pandas, NumPy, scikit-learn, PyTorch).  
• Strong software engineering practices (e.g., version control with Git, unit testing, CI/CD). 
• Be able to translate models into software design functional requirements and specifications. 
• Strong proficiency in SQL for data extraction and analysis. 

Preferred Skills: 

• Experience in the logistics, transportation, or ride-sharing industry. 
• Experience with dynamic or real-time routing algorithms. 
• Big Data Technologies: Hands-on experience with distributed computing frameworks like Apache Spark or Dask. 
• Experience with implementing MLOps practices using MLOps tools and platforms (e.g., MLflow, Kubeflow, Docker, Kubernetes, or cloud equivalents like Azure Machine Learning or Amazon SageMaker). 
• Development experience with back-end software services. Preferably with Microsoft .Net. 

• Medical, Dental, Vision insurance
• Virtual Doctor Visits with $0 Co-Pay
• Life Insurance (company paid)
• Short Term Disability Insurance (company paid)
• Long-Term Disability Insurance (company paid)
• Paid Time Off (PTO)
• Paid Holidays
• Paid Time to Volunteer
• Flex Spending Account (FSA)
• 401K Plan (with an awesome employer match!)
• Employee Assistance Program
• Employee Discounts Program

Since 2006, EverDriven has remained committed to incorporating environmental, social and governance fundamentals into the framework of our internal and external culture. Today, ESG principles are part of the lifeblood of EverDriven and a driving influence that shapes not only our culture but all aspects of our day-to-day operations. We believe ESG principles enable us to more successfully achieve our mission to help every child have an equal opportunity to learn, grow, and succeed.

Commitment to Diversity and Inclusion:

EverDriven is a mission-centered, action-oriented company that honors diversity and inclusion. Our customers come from all walks of life and so do we. We strive to hire great people from a variety of backgrounds, not just because it’s the right thing to do, but because it makes our cultural health stronger. In turn, our inclusive culture inspires our innovation and fosters a sense of belonging so we can continue to serve the most vulnerable populations with excellence.

Commitment to Equal Opportunity:

EverDriven is deeply committed to building a workplace where inclusion is not only valued but prioritized. We’re proud to be an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, family status, marital status, sexual orientation, national origin, genetics, disability, age, or veteran status, or any other non-merit based or legally protected grounds.

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