UnleashX
https://unleashx.aiAbout
We started with a simple question: w̲h̲a̲t̲ i̲f̲ y̲o̲u̲r̲ t̲e̲a̲m̲ c̲o̲u̲l̲d̲ f̲o̲c̲u̲s̲ o̲n̲ w̲h̲a̲t̲ t̲h̲e̲y̲ l̲o̲v̲e̲ m̲o̲s̲t̲?̲
𝐎𝐮𝐫 𝐚𝐧𝐬𝐰𝐞𝐫:
AI voice employees that handle the work nobody wants to do. Customer calls at 11 PM. Follow-ups that slip through the cracks. Onboarding that takes forever. These aren't just tasks—they're the things that keep great people from doing great work.
𝐖𝐡𝐚𝐭 𝐰𝐞'𝐯𝐞 𝐥𝐞𝐚𝐫𝐧𝐞𝐝:
The best technology feels invisible. Our AI employees don't feel like software—they feel like that reliable teammate who just gets things done. No hand-holding, just consistent results that make everyone's day better.
𝐇𝐨𝐰 𝐰𝐞 𝐭𝐡𝐢𝐧𝐤 𝐚𝐛𝐨𝐮𝐭 𝐢𝐭:
This isn't about replacing anyone. It's about giving your team superpowers. When AI handles the repetitive conversations, your people can focus on solving problems, building relationships, and creating things that matter.
𝐖𝐡𝐚𝐭 𝐝𝐫𝐢𝐯𝐞𝐬 𝐮𝐬:
Every business has incredible people doing mundane work. We think that's backwards. So we built AI employees that free up human potential—one conversation at a time.
We're not trying to change the world overnight. We're just making tomorrow a little better than today, for teams who believe work should be meaningful.
Ready to give your team superpowers?
Tech stack
NodeJS (Node.js)
PythonCandid answers by the company
Gurugram
Company social profiles
Jobs at UnleashX
PythonWhat You’ll Do
- Build and enhance real-time voice agents for sales, support, and operations use cases
- Work with ASR, TTS, LLMs, and dialog orchestration frameworks to improve voice quality and response accuracy
- Integrate multiple providers (Deepgram, Sarvam, ElevenLabs, OpenAI) into a modular voice pipeline
- Reduce latency, improve interrupt handling, and make conversations more natural
- Own the agent evaluation process: call audits, response quality scoring, and accuracy improvements
- Collaborate with product teams and customers to understand real call behaviours and solve friction points
- Contribute to voice infrastructure: WebRTC, streaming sockets, call routing flows
⚙️ What You Bring
- 3–6 years of experience as an AI/ML/LLM Engineer working on voice or conversational systems
- Strong hands-on experience with LLM prompting, finetuning, embeddings, and RAG
- Solid understanding of STT and TTS models and tuning them for natural speech
- Proficiency in Python and Node.js
- Experience with real-time audio streaming (WebRTC, WebSockets) is a strong advantage
- Ability to debug live calls and rapidly improve agent behaviour
- Strong sense of ownership and willingness to iterate closely with users
🏆 What Success Looks Like
- Voice agents handle interruptions smoothly and sound natural
- Call success and customer completion rates increase month over month
- Latency, token usage, and infra costs are reduced through better engineering and smart model choices
- Customers begin trusting agents as teammates, not just tools
If You Are Someone Who:
✅ Builds fast and learns faster
✅ Cares deeply about product experience, not just model performance
✅ Wants to create the future of how businesses talk to customers
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