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Salary: USD 140,000 - 185,000 / annual
Firestorm is building next-generation uncrewed aircraft and advanced manufacturing systems. The Software Integration & Operations department owns the software layer spanning factory floor to cloud—applications, automation, edge systems, and intelligence that enable rapid product iteration, manufacturing automation, and scaled production.
You will own the algorithms and systems behind the manufacturing platform's intelligence layer: a planning workbench, simulation engine, analytics surface, and AI assistant that transforms operational data into better decisions.
Key responsibilities:
- Own optimization algorithms for the planning workbench and simulation engine: work order scheduling, resource allocation, constraint satisfaction, and conflict resolution
- Design and implement the analytics layer: defect trends, yield analytics, throughput modeling, and operational intelligence
- Lead AI assistant integration: select, evaluate, deploy, and fine-tune open-source or custom LLMs for cloud, air-gapped, and on-edge (DoD) contexts
- Productionize optimization and ML systems in partnership with full-stack and infrastructure engineers—reliable services, not prototypes
- Partner with manufacturing engineering, quality, and planning domain experts to ground models in real operational constraints
- Evaluate build-vs-buy decisions across optimization libraries, ML tooling, and model vendors
Required: Bachelor's in Computer Science, Engineering, or equivalent; U.S. citizenship (ITAR); 5+ years engineering with substantial applied optimization, operations research, or ML systems work; deep Python proficiency and fluency with optimization frameworks (MILP solvers, constraint solvers, OR-Tools); proven track record productionizing algorithmic systems; strong applied math foundation in combinatorial optimization, heuristics, or statistical modeling; ability to partner with domain experts and translate operational constraints into models; demonstrated commitment to high standards.
Preferred: prior scheduling/planning/resource allocation systems experience in manufacturing or logistics; hands-on LLM deployment (Llama, Mistral); air-gapped or on-edge deployment background; discrete-event or agent-based simulation experience; defense, aerospace, or regulated industry background.
