SlipstreamJobs tracks this role from the company's public career site. Apply directly on the employer's site.
Salary: USD 150,000 - 220,000 / annual
Firestorm is building expeditionary defense manufacturing and autonomous systems, including modular unmanned aircraft and deployable microfactories (xCell). The company addresses a critical gap: modern warfighters need systems that are rapidly deployable, affordable, and producible at scale.
Crucible is Firestorm's manufacturing operations software—a unified platform combining production planning, execution, supply chain, and manufacturing data. As Staff ML Engineer for Applied AI, you will architect and ship AI capabilities that power this platform.
You will work across data science and software engineering to:
- Develop AI-assisted workflows leveraging Crucible's data, APIs, and domain model to surface insights and support decision-making
- Productionize optimization, forecasting, and other decision models into reliable product features
- Build end-to-end AI systems: model interfaces, retrieval, tool use, orchestration, evaluation, and production services
- Select and evaluate models based on capability, reliability, latency, security, and deployment constraints
- Support AI in constrained environments (cloud, air-gapped, edge) where external APIs may not be available
- Partner with manufacturing, supply chain, and product teams to translate operational problems into useful AI features
- Establish technical patterns, evaluation methods, and engineering standards for AI across Crucible
This is a hands-on engineering role focused on shipping reliable, measurable AI—not research. You will own the full lifecycle from experimentation through production debugging and monitoring.
Required: U.S. citizenship and ability to obtain/maintain a security clearance. 5+ years shipping production software or ML systems. Strong ML fundamentals beyond API integration. Proven technical ownership of AI/ML systems from experimentation through production. Hands-on experience with LLMs or foundation models in production. Strong Python and software engineering. Experience with modern ML frameworks, transformer models, production evaluation, and monitoring. Demonstrated ability to balance model quality, reliability, latency, cost, and complexity.
Preferred: Open-source and local model inference, manufacturing/supply chain/logistics software, model fine-tuning, inference optimization, GPU deployment, aerospace/defense/robotics/complex systems experience.
Based in San Diego, CA. Relocation assistance available.
