Application Developer – AI/ML & Sensor Fusion
Listed on 2026-01-02
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IT/Tech
AI Engineer, Machine Learning/ ML Engineer
Husmann Technologies specializes in offering effects-based solutions. We are developing next-generation predictive maintenance operational awareness solutions using multiple sensor modalities with advanced machine learning, generative AI, and AI agents.
We are located in North Oklahoma City, OK - Oklahoma City offers a rare combination that’s increasingly hard to find for developers: real technical work, real impact, and a high quality of life without the coastal burn rate. OKC has quietly become a hub for advanced aerospace, defense, energy, and AI-driven engineering, where developers ship systems that matter. The cost of living is low enough that your compensation goes further—owning a home, having space to think, and time to build—while still enjoying a growing tech community, an accessible airport, great food, and an easy daily rhythm.
For developers who want to focus on solving meaningful problems, grow into technical leadership faster, and build something lasting without sacrificing their lifestyle, OKC is an unusually strong place to do it.
This is a full-time, on-site role for an Application Developer – AI/ML & Sensor Fusion, based in Edmond, OK. The role involves developing, integrating, and maintaining software applications with a focus on AI/ML algorithms and sensor fusion. Day-to-day tasks include designing and implementing software solutions, working with programming languages, managing and optimizing database systems, and collaborating with teams to ensure seamless integration of technologies.
Qualifications- Experience with PyTorch, scikit-learn, and CUDA
- Experience with generative AI and AI agents
- Familiarity with RL and RLHF
- Understanding of signal processing concepts
- Proven experience in Machine Learning lifecycle operations
- DoD or industrial systems experience
- Design and develop Python-based applications for edge, hybrid, and cloud deployments
- Implement ML/DL models using PyTorch and scikit-learn
- Support pre-training, labeling, fine-tuning, and RLHF workflows
- Integrate generative AI systems and AI agents
- Implement Acoular-based acoustic processing and sensor fusion
- Document architecture and support demonstrations
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