Forward Deployed Industrial Engineer, Defense Logistics AI

The Marine Corps moves people, parts, and equipment around the world on timelines that don't forgive guesswork. We build the AI systems that help them do it - reinforcement learning-based planning and optimization software deployed inside real military logistics operations, from Marine Logistics Groups to Blount Island Command.

This role sits at the seam between our software and the operations it runs on. You'll be the person who turns messy, real-world logistics and maintenance data into the signal that drives both better day-to-day decisions for our customers and a smarter product for everyone who comes after them. If you've ever wanted your analytical work to actually change how something operates - not just live in a dashboard nobody opens - this is that job.

Responsibilities

• Embed with military logistics, supply and maintenance operations to understand how decisions get made today - and where AI, automation, and better instrumentation can change the math.
• Turn operational data (logistics, maintenance, readiness, inventory) into the analyses, dashboards, and models that customer leadership actually uses to run their organizations.
• Build the data pipelines, ETL, and integrations that connect customer ERP, MES, CMMS, and logistics systems to our platform - and keep them running in restricted environments.
• Partner with our RL and platform engineers to translate operational reality into product: what the optimizer needs to know, what "good" looks like, and where our models are leaving value on the table.
• Run the quantitative work behind capacity planning, forecasting, simulation, and process redesign - and then carry the recommendations across the finish line into deployed change.
• Be the credible technical voice in front of senior military and civilian stakeholders who need to trust both you and the system.

Desired Skills

• A degree in Industrial Engineering, Systems Engineering, Operations Research, or a closely related quantitative field.
• 2+ years working on real operational problems - manufacturing, logistics, maintenance, supply chain, or similar - not just coursework or pure analytics.
• Strong Python (pandas, NumPy, the usual suspects) and SQL chops. You can move from a question to a clean answer without three meetings in between.
• Experience building dashboards people actually use (Power BI, Tableau, Grafana, or similar).
• The ability to explain a model, a tradeoff, or a recommendation to someone who has never opened a Jupyter notebook - and have them leave the room more confident, not less.
• US citizenship and the willingness to work toward a security clearance. Existing clearance is a plus, not a requirement.

Bonus Points

• Prior work in defense, government, or other regulated environments - or military service yourself.
• Cloud (AWS or Azure), APIs, ETL, and systems integration experience.
• Background in optimization, statistical modeling, simulation, or applied ML.
• Lean / Six Sigma fluency from somewhere it actually mattered.
• Comfort working in austere or air-gapped environments.

What Success Looks Like in Year One

• Customer decisions that used to run on spreadsheets and tribal knowledge are running on data you helped instrument.
• The product team is shipping features that came directly from patterns you spotted on the ground.
• Manual reporting that used to eat days of analyst time is automated and trusted.
• When senior leadership at a customer command wants to know how their logistics operation is really performing, the answer comes from a system you helped build.