Senior Voice AI / Speech ML Engineer

Experience: 3–4 years
Employment: Full-time
Location: HSR Layout Bengaluru | On-site
About the Role
We are looking for a Senior Voice AI / Speech ML Engineer to join our AI team and build the next generation of speech and voice intelligence systems.
This role is for an engineer/researcher who has hands-on experience training large-scale speech or language foundation models, not just integrating or fine-tuning existing models.
You will work across ASR, TTS, speaker identification, VAD and conversational AI, taking models from large-scale data preparation and training through evaluation, optimization and production deployment.
If you have personally trained/pre-trained a foundation model and have strong ASR/TTS experience, we would like to hear from you.
What You'll Work On
Design, train, pre-train and fine-tune foundation models for Voice AI.
Develop and train ASR and/or TTS models for real-world speech applications.
Work with large-scale speech, audio and text datasets.
Build data preparation, preprocessing, augmentation and model-training pipelines.
Design experiments and evaluate models across accuracy, robustness and generalization.
Improve WER/CER, speech quality, latency and inference efficiency.
Work with Transformer-based architectures and modern speech-model architectures.
Train models using GPUs and distributed computing infrastructure.
Debug training instability, data issues and model-performance bottlenecks.
Optimize trained models for production, including quantization and inference optimization.
Collaborate with research and engineering teams to move models from experimentation to production.
Must-Have Experience
3–4 years of hands-on experience in Speech ML, Speech AI, NLP, Deep Learning or Machine Learning.
Actual foundation-model training/pre-training experience.
Hands-on experience developing or training ASR and/or TTS models.
Strong understanding of Transformers and deep learning.
Strong Python programming skills.
Hands-on experience with PyTorch and/or TensorFlow.
Experience with GPU-based model training and large datasets.
Strong understanding of model evaluation, experimentation and optimization.
Strongly Preferred
Experience with one or more of:
Whisper
wav2vec 2.0
HuBERT
Conformer / FastConformer
NVIDIA NeMo
SpeechBrain
Hugging Face
F5-TTS / VITS / similar TTS architectures
Speech or audio foundation models
Multilingual / low-resource speech
Indian-language speech datasets
Distributed training using DeepSpeed, FSDP, Ray Train or similar
Audio preprocessing, augmentation, annotation and dataset-quality pipelines
Production deployment of speech models
What We Are Specifically Looking For
The ideal candidate has worked on the model itself, rather than only building applications around existing models.
Strong fit:
Foundation-model pretraining + ASR/TTS + Transformers + PyTorch + GPU/distributed training + large-scale speech data
Not the right fit:
Generic ML Engineer without speech experience
GenAI / RAG Engineer
Prompt Engineer
LLM application developer
Candidates who only consume OpenAI/Claude/Gemini APIs
Candidates who only fine-tune existing pretrained models
Conversational AI developers who integrate speech APIs/Riva/voice APIs but don't train speech models
Candidates with only NLP/LLM experience and no ASR/TTS
Why Join
Work on core Voice AI / Speech ML technology, not only application-layer GenAI.
Solve challenging problems involving large-scale model training, speech data and inference optimization.
Work closely with AI/ML engineers and researchers on production-grade models.
Opportunity to work on multilingual and real-world speech applications in a high-growth AI environment.

Work arrangement
No