**Role Description:**
You will aid in designing the optimization core of Haladir’s products, including the models that decide how waves get released, how inventory gets allocated, how routing occurs within trucking networks, and how labor gets planned inside 3PL operations. Our approach combines practical heuristics, including local search and hill climbing, with solver-based methods such as MILP and constraint programming where they are the right tool.
You will take messy operational constraints from real customers and turn them into formulations and systems that run in production under real-world deadlines. You will work closely with operators to understand how decisions are actually made, determine what should be optimized, and build models that can make those decisions reliably at scale.
This is applied research with execution authority. Your models will make decisions that operators act on the same day.
**Required Qualifications:**
- Strong background in Operations Research, including MILP, constraint programming, heuristics, and local search
- Research experience in Operations Research through publications, graduate research, or equivalent applied work
- Able to implement your own models in production-quality Python using solver APIs such as Gurobi, CP-SAT, or HiGHS
- Able to turn real-world operational constraints into mathematical models that can run in production
- Strong judgment around solution quality, computational performance, and real-world operational constraints
- Willingness to relocate to San Francisco and travel to customer sites
- US work authorization
**Preferred Qualifications:**
- Currently enrolled or finished Bachelors/MS or PhD in Operations Research, Industrial Engineering, Applied Mathematics, or a related quantitative field
- Domain experience in warehousing, routing, scheduling, or supply chain
- Experience deploying optimization models in live operational environments
- US citizen
Visa sponsorship is not available for this role.
