Job Description

Drive frontier research in speech-to-speech and multimodal AI systems to build natural, self-learning, voice-capable AI Workers.

Company details

GoCommotion is a fast-growing startup revolutionizing Customer Experience (CX) with AI Workers -- persistent, multimodal agents capable of real-time, contextual conversations across channels. We blend LLMs, voice modeling, and agentic reinforcement to build truly autonomous AI systems.

Website: https://www.gocommotion.com/

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

Important Note

ClanX is a recruitment partner, helping GoCommotion hire the Senior Machine Learning Engineer.