Who We’re Looking For
We are not looking for someone who is just “familiar” with Conversational AI. We need an exceptional engineer ready to embed with a proven track record in building, deploying, and optimizing Conversational AI models at scale—not just in research environments, but in real-world, operational AI deployments for customer service or highly-regulated industries.
You should apply if:
✅ You have led the development of high-accuracy conversational AI models that drive measurable efficiency gains.
✅ You have deployed models into production at scale—not just in R&D or sandbox environments.
✅ You understand the limitations of LLMs and NLP models in real-world voice AI and know how to overcome them.
✅ You have deep expertise in ASR (Automatic Speech Recognition), NLP, and voice AI automation—not just chatbot experience.
If you haven’t built AI models that are live in production, this role is not for you.
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What You’ll Work On
• Develop and optimize high quality and accurate Conversational AI agents that drive real automation, not just assistive suggestions.
• Engineer real-time AI-driven call handling workflows that reduce agent handle time and improve citizen experience.
• Advance speech recognition and language models that handle high-variance, real-world voice inputs.
• Deploy AI models using MLOps best practices to ensure reliability, scalability, and compliance.
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What Makes Someone Excellent in This Role?
• Track record of production-level AI deployments—your AI is used in real environments and drives measurable efficiency gains.
• Deep domain expertise in NLP and voice AI—you understand conversational AI failures and how to improve them.
• Proven ability to build AI that integrates into real workflows—this is not just about research, it’s about execution.
• Experience in high-stakes AI deployment—working with regulatory, compliance-heavy environments is a strong plus.
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Project Details
• Engagement Type: Open to fixed-price projects or ongoing hourly work, depending on expertise and fit.
• Location: U.S.-based preferred (DC/Oakland a plus), but open to strong remote candidates.
• Timeline: Immediate need.
📌 To Apply:
• Provide a portfolio of AI deployments, including evidence of models deployed in production.
• Share GitHub repos, case studies, or live AI models in use today.
• Indicate your availability and preferred work structure.
