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Role Description:
You will aid in designing the optimization core of Haladir’s products, including, for example, the models that decide how waves get released, how inventory gets allocated, how routing occurs within trucking networks, and/or 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 and turn them into formulations and systems that run in production under real-world deadlines. You will work closely with operator's problems to understand how decisions are actually made, determine what should be optimized, and build models that can make those decisions reliably at scale.
This role offers greater autonomy and closer collaboration with the founding team than other positions.
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 potential customer sites
US work authorization
Preferred Qualifications:
Currently enrolled or finished 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
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