Senior Data Scientist

Requirements

3+ years of applied or academic experience in speech, multimodal, or LLM research

Bachelor's or Master's in Computer Science, AI, or Electrical Engineering

Strong in Python and scientific computing, including JupyterHub environments

Deep understanding of LLMs, transformer architectures, and multimodal embeddings

Experience in speech modeling pipelines: ASR, TTS, speech-to-speech, or audio-language models

Knowledge of turn-taking systems, VAD, prosody modeling, and real-time voice synthesis

Familiarity with self-supervised learning, contrastive learning, and agentic reinforcement (ART)

Skilled in dataset curation, experimental design, and model evaluation

Comfortable with tools like Agno, Pipecat, HuggingFace, and PyTorch

Exposure to LangChain, vector databases, and memory systems for agentic research

Strong written communication and clarity in presenting research insights

High research curiosity, independent ownership, and mission-driven mindset

Currently employed at a product-based organisation

Responsibilities

Research and develop direct speech-to-speech modeling using LLMs and audio encoders/decoders

Model and evaluate conversational turn-taking, latency, and VAD for real-time AI

Explore Agentic Reinforcement Training (ART) and self-learning mechanisms

Design memory-augmented multimodal architectures for context-aware interactions

Create expressive speech generation systems with emotion conditioning and speaker preservation

Contribute to SOTA research in multimodal learning, audio-language alignment, and agentic reasoning

Define long-term AI research roadmap with the Research Director

Collaborate with MLEs on model training and evaluation, while leading dataset and experimentation design

Job Details

Location: Hybrid Mumbai, Bengaluru, Chennai, India

Interview process

Screening / HR round

Technical round(s) coding, system design, ML case studies

ML / research deep dive

Final / leadership round