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Job Description
Structured overview of role & requirementsAbout This Role
Research, design, fine-tune, and evaluate foundation AI models (LLMs, ASR, TTS) for conversational call agent platform.
Develop end-to-end fine-tuning pipelines using techniques like SFT, DPO, LoRA, QLoRA and implement robust model evaluation frameworks.
Collaborate with MLOps for model deployment and adapt models for Indian languages including Hindi and regional accents.
Minimum Requirements
2–3 years hands-on experience in ML model development focusing on LLMs, ASR, or TTS.
Proficiency in PyTorch and experience with HuggingFace ecosystem (Transformers, PEFT, TRL, Datasets).
Experience in fine-tuning techniques such as SFT or DPO.
Location requirement: Bangalore-based role with 5 days/week in-office work.
Ideal Candidate Profile
Experienced in building maintainable, modular Python pipelines and designing structured experiments for model evaluation.
Understands model architecture trade-offs including parameter size, attention mechanisms, KV cache behaviour, and quantization sensitivity.
Familiar with finetuning Whisper-family ASR, neural TTS, or open-source LLMs, synthetic data pipelines, and experiment tracking tools like Weights & Biases or MLflow.