AI Scientist – Conversational
2 weeks ago
About Zudu AI
Zudu AI is building the next generation of
human-like voice automation
that replaces traditional call centers. Our AI agents handle complex customer interactions, understand context, and respond naturally across multiple languages and accents. We work with enterprises and CPaaS providers to deliver scalable, intelligent voice solutions that continuously learn and improve.
Role Overview
We are seeking an
AI Scientist
to design, build, and optimize advanced
speech and conversational AI models
— spanning ASR, TTS, LLM fine-tuning, RAG pipelines, and emotion-driven voice synthesis. You'll work with large-scale data, production systems, and next-gen architectures to make our agents sound truly human.
Key Responsibilities
- Research & Development
- Develop and fine-tune speech recognition (ASR)
,
text-to-speech (TTS)
, and
natural language understanding (NLU)
models. - Build
multi-turn conversational AI systems
capable of contextual reasoning, grounding, and emotional intelligence. - Explore and implement
retrieval-augmented generation (RAG)
and
memory-based dialogue systems
for long-term contextuality. - Research
prosody, emotion, and style transfer
in speech synthesis for natural human-like delivery. - Evaluate and integrate open-source models (e.g., Whisper, Bark, FastSpeech, VITS, GPT-family models).
- System & Data Integration
- Work closely with platform engineers to deploy models in low-latency, production-grade
environments. - Optimize
inference performance
on cloud and edge systems using quantization, distillation, and caching strategies. - Collaborate with the voice pipeline team to align model outputs with
telephony and CPaaS audio protocols
. - Experimentation & Evaluation
- Design and conduct experiments to benchmark accuracy, naturalness, latency, and engagement
. - Lead
data annotation and synthetic voice data generation
projects to improve training quality. - Publish findings internally (and externally when possible) to maintain Zudu AI's leadership in enterprise voice automation.
Preferred Qualifications
- Master's or Ph.D. in
Computer Science, AI, Speech Processing, or Computational Linguistics
. - Strong background in
deep learning
,
transformer architectures
, and
reinforcement learning
. - Hands-on experience with
PyTorch
,
TensorFlow
, or
JAX
. - Expertise in one or more of the following areas:
- Automatic Speech Recognition (ASR)
- Text-to-Speech (TTS)
- Natural Language Processing (NLP)
- Multimodal or Emotion-aware AI
- Understanding of
LLM fine-tuning
,
prompt engineering
, and
retrieval systems (RAG, FAISS, Milvus)
. - Experience deploying models with
Kubernetes
,
TorchServe
, or
ONNX Runtime
. - Familiarity with
speech datasets
,
phoneme-level modeling
, and
accent adaptation
.
Nice-to-Have
- Prior experience in
telephony or conversational AI products
. - Contributions to
open-source speech or NLP projects
. - Understanding of
low-latency voice streaming pipelines
(e.g., gRPC, WebRTC). - Exposure to
emotion detection
,
sentiment analysis
, or
paralinguistic research
.
Soft Skills
- Curiosity and scientific rigor.
- Ability to translate research into
deployable, scalable solutions
. - Collaborative mindset — able to work with engineers, product leads, and linguists.
- Excellent written and verbal communication.
-
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