AI/NLP Developer

What You’ll Build
You’ll be part of the core team developing a real-time, voice-first AI assistant that:
• Listens with a wake-word and speech recognition
• Understands complex field commands using local NLP or LLM-based pipelines
• Responds instantly—even in offline or poor-signal conditions
• Powers real-world workflows where time and clarity are critical
Key Responsibilities:
• Deploy and optimize lightweight transformer-based models for execution on embedded or edge-class computing platforms
• Design local retrieval-augmented generation (RAG) pipelines using structured, indexed data
• Build and refine wake-word, speech-to-text (STT), and text-to-speech (TTS) modules
• Create conversational command flows integrated with existing embedded software systems
• Ensure all AI systems operate offline, securely, and with minimal latency
• Collaborate closely with internal product, engineering, and AI teams to evolve capabilities
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What You Bring
You're not just an AI engineer—you know how to build smart systems that run fast, locally, and reliably, even when the network drops or the pressure’s on.
Must-Have Skills:
• Proven experience deploying transformer-based models on resource-constrained devices (e.g., embedded processors or low-power compute modules)
• Familiarity with quantized or distilled models (e.g., TinyLLaMA, GPTQ, GGUF, DistilBERT, Whisper.cpp)
• Strong Python skills; C++ or Rust experience for embedded or low-latency optimization
• Experience with wake-word, speech-to-text, and text-to-speech integration
• Experience building offline RAG systems using local vector search (FAISS, ChromaDB)
• Knowledge of prompt design and orchestration logic for compact inference engines
• Security-conscious development practices for offline AI applications
Bonus Experience:
• NLP or embedded AI in public safety, defense, automotive, or mission-critical systems
• Experience working with LangChain-style orchestration, adapted for offline edge use
• Voice-first UI/UX experience in screen-free or touchless environments
• Familiarity with optimizing inference for fanless, ruggedized, or mobile AI devices
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The Role
• Type: Contract-to-Hire (option to grow into a leadership role)
• Location: Remote (U.S. preferred)
• Start Date: Immediate
• Compensation: Competitive and impact-based
• Team: High-caliber, low-ego, mission-driven professionals focused on outcomes
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Why This Role Matters
You won’t be tuning cloud prompts or building toy copilots. You’ll be creating real-world, on-device AI that delivers fast, meaningful decisions at the edge—where they’re needed most.
If you’re tired of watching smart systems stall in theory and want to build one that works in practice, this is the place.