Founding ML Engineer

Batch: 2019/2020/2021/2022/2023. Required Skills: - 3+ years of hands-on ML experience with deep practical real-world experience in training models. - Strong Python and PyTorch fundamentals with exposure in distributed training, and modern fine-tuning techniques (LoRA, QLoRA, DPO, RLHF, etc.). - Training data as a first-class problem. Experience designing data pipelines from collection, cleaning, labeling, deduplication, augmentation and treating data quality as a core engineering discipline. - Rigorous about evaluation. You know that "looks good in a demo" is not a benchmark. You build the evals before you trust the model. - Speech model experience is a plus with real-time / streaming inference experience where you would have contributed to latency optimization, quantization, and distillation for production deployment. - Bias toward shipping. You'd rather have a model running in production this week than a perfect one in a notebook next quarter. Preferred Skills: - Speech and real-time ML expertise: Experience working with speech, audio, multimodal, or real-time machine learning systems. - Voice AI domain knowledge: Hands-on experience with ASR, TTS, VAD, language identification, speaker systems, or conversational turn-taking. - Multilingual model development: Experience building and evaluating multilingual models, particularly for Indian languages. - Inference optimisation: Experience with streaming inference, latency optimisation, quantisation, distillation, or model compression for production deployment.