What are the responsibilities and job description for the PhD Operations Research Specialist position at Arrive AI Inc.?
Company:
At Arrive AI (Nasdaq: ARAI), we're not just building products—we're transforming the future of the Autonomous Last Mile™ (ALM). Over a decade ago, we started with a pioneering vision and patents for the first smart mailbox for drone delivery. Through systematic research, development, and deep customer collaboration, we've evolved to today where we deploy Arrive Points—a type of smart locker and mini-cross-docks for frictionless drone, robotic, and courier delivery and pickup, utilized from medical supplies to meals to e-commerce. Arrive AI is now growing and investing to scale an ALM network and platform of the future for all autonomous delivery providers, services, and customers. Arrive AI is the intelligent choice for the last inch of the Autonomous Last Mile™.
About Us:
We move fast, balancing strategy with opportunity. We are merit-based, valuing integrity, innovation, and treating others as we want to be treated. At Arrive AI, every employee is an equity holder and a business owner. Our shared vision, ownership, and culture fuel our mission to revolutionize autonomous delivery.
Product Team
You’ll be joining Arrive AI’s Product Team to revolutionize Autonomous Last Mile (ALM) logistics by transforming over a decade of research, design, and customer collaboration into the world’s first autonomous logistics network and platform. Our fast-paced skunkworks team rapidly iterates, prototypes, and develops next-generation Arrive Point units, networks, and AI-powered platforms. By integrating cutting-edge hardware, robotics, IoT, software, data, AI, and manufacturing, we’re driving a bold roadmap for ALM innovation. Based in Fishers, IN, we offer a unique opportunity to do your life’s best work, shape the future, and share in the success.
The Role:
We’re seeking a PhD Operations Research Specialist to design and optimize the mathematical backbone of Arrive AI’s ALM platform. You’ll create the models, algorithms, and decision frameworks that power how drones, robots, couriers, and lockers interact—from routing and scheduling to inventory placement and marketplace dynamics.
This is a role for someone who loves turning complex, multi-variable logistics challenges into solvable models, and who wants their work to directly impact the efficiency, economics, and scalability of an emerging autonomous delivery network.
What You’ll Do
- Model Complex Operations: Develop optimization and decision models for core ALM challenges:
- Multi-modal routing and scheduling for drones, robots, and couriers.
- Inventory positioning and dynamic stocking for Arrive Points across a region.
- Marketplace balancing for multiple delivery partners, customers, and services.
- Capacity allocation and real-time dispatch for mixed fleets.
- Design Algorithms for Scale: Create algorithms for large-scale combinatorial problems (e.g., vehicle routing, stochastic demand planning, facility location).
- Integrate OR AI: Collaborate with data scientists and AI engineers to combine predictive models (e.g., demand forecasts) with prescriptive optimization for actionable decisions.
- Simulate & Validate: Use digital twins and scenario simulations to test optimization strategies against real-world constraints (weather, traffic, service-level targets).
- Optimize Trade-Offs: Develop models that balance cost, speed, carbon footprint, and service reliability to align with business and regulatory goals.
- Provide Strategic Insights: Translate modeling results into roadmaps and decision frameworks for product managers, engineers, and leadership.
- Collaborate Cross-Functionally: Work closely with engineering, robotics, and product teams to ensure models are practical, implementable, and drive measurable improvement.
Requirements:
What We're Looking For:
- Advanced Education: PhD in Operations Research, Industrial Engineering, Applied Math, or a related field.
- Research-to-Application Experience: 3 years of experience applying OR in real-world systems (logistics, transportation, supply chain, or marketplaces).
- Optimization Expertise: Deep knowledge of linear, integer, stochastic, and network optimization, plus familiarity with routing, scheduling, and facility location problems.
- Programming & Tools: Proficiency in Python, Julia, or similar, with hands-on experience using optimization libraries (CPLEX, Gurobi, OR-Tools).
- AI OR Fluency: Understanding of how machine learning and AI (e.g., demand prediction, clustering, reinforcement learning) can be integrated into optimization workflows.
- Preferred Domains: Exposure to multi-modal logistics, autonomous systems, or marketplace modeling is a big plus.
- Innovative Thinking: Ability to formulate new problems, explore trade-offs, and craft algorithms that deliver practical impact.
- Collaborative Spirit: Skilled at working with multidisciplinary teams—turning abstract math into concrete, scalable systems.
- Adaptability: Thrives in a fast-paced, exploratory environment where new constraints and opportunities emerge rapidly.
Additional:
- Expect to travel up to 5 days per month.
- Responsibilities include all other duties as assigned.
Compensation:
- Salary is market competitive with high equity incentive – be an owner and grow with Arrive AI.
