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Operations Research Engineering Intern (Fall 2026)

Haladir

San Francisco, CAInternship$6,000–8,000/moPosted 3w agoStill listed 2w ago

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At a glance

Compensation
$6,000–8,000/mo
Location
San Francisco, CA
Role Type
Internship
Work Authorization
US work authorization required

Olive lists jobs from US employers, including remote roles you can work from the United States.

Job overview

The intern will assist in designing Haladir’s optimization core, creating models for wave release, inventory allocation, routing, and labor planning. They will translate complex operational constraints into production‑ready formulations, collaborate with operators to understand decision processes, identify optimization targets, and develop scalable models that meet real‑world deadlines.

Skills & qualifications

RequiredNice to have

Skills

Operations ResearchMILPConstraint ProgrammingHeuristicsLocal SearchPythonGurobiCP-SATHiGHS

Qualifications

Strong Background in Operations ResearchResearch Experience in Operations Research Through Publications, Graduate Research, or Equivalent Applied WorkAbility to Implement Models in Production-Quality Python Using Solver APIsAbility to Turn Real-World Operational Constraints Into Mathematical ModelsStrong Judgment Around Solution Quality, Computational Performance, and Real-World Operational ConstraintsWillingness to Relocate to San Francisco and Travel to Potential Customer SitesUS Work AuthorizationCurrently Enrolled or Finished Bachelor's or MS or PhD in Operations Research, Industrial Engineering, Applied Mathematics, or Related Quantitative FieldDomain Experience in Warehousing, Routing, Scheduling, or Supply ChainExperience Deploying Optimization Models in Live Operational Environments

Full job description

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.

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 Bachelor's or 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

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