ML Researcher / Engineer - Voice and Speech to Speech Models

Location: Bengaluru (Work from Office - Domlur)

Team: AI & Machine Learning

Experience: 2–7 years

What You'll do:

• Fine-tune and deploy LLMs, TTS, STT, and voice models for use in real-time conversations with millions of users.

• Convert unstructured, messy real-world audio/text data into clean, high-quality datasets for training and evaluation.
• Build inference pipelines optimized for low-latency, high-accuracy voice agents and multimodal interfaces.
• Work closely with infra and product teams to ship production-grade GenAI models with observability, fallback, and monitoring.
• Experiment with GANs, diffusion models, audio generation, and multimodal fusion to power next-gen AI agents.
• Own the full model lifecycle — from research and training to deployment, testing, and iteration.

What we're Looking for:

• 2-7 years of hands-on experience in AI / ML roles, ideally in startups or product-driven teams.
• Strong grasp of LLM fine-tuning, instruction tuning, or pretraining techniques.
• Familiarity with TTS/STT systems, Whisper, Tacotron, VITS, or other open source models .
• Experience with multimodal architectures, generative audio, GANs, or diffusion-based models.
• Ability to work with real-world messy data, design training pipelines, and debug model failure modes.
• Fluency in frameworks like PyTorch, HuggingFace, TensorFlow, and ecosystem tools (ONNX, Triton, LangChain, etc.).
• Passion for building high-impact AI features that ship to real customers.
  

Requirements

Why Join Us:

• Work at the cutting edge of LLMs, voice AI, and generative models — and ship real products, not just prototypes.

• Directly impact millions of users by powering AI agents that help with hiring, learning, and career growth.
• Collaborate with a world-class team of AI engineers, researchers, and product minds who move fast and ship boldly.
• Freedom to explore: Own experiments, propose architecture, or contribute to foundational model training.
• Startup speed, enterprise scale — best of both worlds. Rapid iteration and direct customer feedback.
• Multilingual India - first problems that push the boundaries of speech, reasoning, and personalization.