What You'll Do - Own the optimization algorithms behind the planning workbench and simulation engine - scheduling, resource allocation, constraint satisfaction, conflict detection.
- Design and implement the analytics layer of the platform: defect trends, yield analytics, throughput modeling, and operational intelligence.
- Lead the platform's AI assistant integration: selecting, evaluating, deploying, and fine-tuning open-source or custom LLMs for cloud, air-gapped, and on-edge contexts.
- Productionize optimization and ML systems in partnership with full-stack and infrastructure engineers - reliable services the platform depends on, not prototypes.
- Partner with domain experts in manufacturing engineering, quality, and planning to ground models and algorithms in real operational constraints.
- Evaluate and advocate for build-vs-buy decisions across optimization libraries, ML tooling, and model vendors.
Required Qualifications - Bachelor's degree in Computer Science, Engineering, or related field (or equivalent practical experience)
- U.S. Citizenship required due to ITAR regulations
- 5+ years of engineering experience with substantial applied optimization, operations research, or ML systems work.
- Deep proficiency in Python; fluency with at least one optimization framework - MILP solvers, constraint solvers, OR-Tools, or equivalent.
- Track record of productionizing algorithmic systems - you have shipped optimization or ML into real users' hands, not just research artifacts.
- Strong applied math foundation: combinatorial optimization, heuristics, or statistical modeling relevant to scheduling and resource allocation problems.
- Demonstrated ability to partner with domain experts and translate operational constraints into model formulations.
- Demonstrated history of holding yourself and your teammates to a high standard, even when it creates discomfort.
Preferred Qualifications - Prior experience building scheduling, planning, or resource allocation systems for manufacturing, logistics, or similar domains.
- Hands-on experience deploying or fine-tuning open-source LLMs (Llama, Mistral, or similar) for constrained environments.
- Background with air-gapped or on-edge model deployment.
- Familiarity with discrete-event simulation or agent-based modeling.
- Prior experience in defense, aerospace, or regulated industry applications.
Work Environment - Remote (U.S.) with the option to be based at our Headquarters in San Diego, CA. We welcome candidates who are local or open to relocating; relocation assistance is available and may be included in the offer package where appropriate
- Willingness to travel up to 10% domestically for testing and demonstrations
CompensationUS Salary Range: $140,000 - $185,000 USD
The posted salary range reflects an estimate based on a variety of compensation factors, including but not limited to relevant experience, education, certifications, specialized skills, geographic location, and business needs. Actual compensation may vary, and this range is subject to change as our compensation structure or market conditions evolve.
Benefits & PerksOur culture fosters collaboration, respect, and trust, empowering passionate people to do their best work. We offer a competitive salary, comprehensive benefits, and opportunities for career growth. In addition to an opportunity to take part in an innovative, collaborative and fast-growing business with a highly motivated and skilled team, we also take pride in taking care of our employees. Here are just a few ways that we show our appreciation:
- We offer comprehensive medical, dental, and visions plans
- 401(k) Retirement Savings Plan to invest in your long-term retirement goals
- Equity grants for new hires
- Unlimited PTO
- Extremely generous company holiday calendar, including a holiday hiatus in November, & December
- Generous Parental Leave
- Lifestyle Spending Account
- FSA
- DCFSA
- HSA
- Hospital Indemnity insurance
- Critical Illness insurance
- Accident insurance
- Basic Life/AD&D, short-term and long-term disability insurance, 100% covered by Firestorm. Plus, the option to purchase additional life insurance for you and your family
- Mental Health Resources: We provide free mental health resources 24/7 including therapy and more. Additional work-life services, such as free legal and financial support, are available to you as well
CompensationThe base pay range for this role is $140,000 - $185,000 per year.
