Machine Learning Engineer

Responsibilities:

1. Build the data engine - Design pipelines to source and clean conversational voice data across Indian languages, accents, and telephony conditions.
2. Fine-tune models that ship - Fine tune and train models to improve accuracy, speed, and reliability across different use-cases.
3. Define what "good" means - Build evaluation datasets and benchmarks for transcription accuracy, voice naturalness, interruption handling, latency, and end-to-end conversation quality. Set up human-in-the-loop pipelines to capture subjective quality at scale.
4. Ship to production - Work with the engineering team to deploy models into a latency-sensitive, high-volume system. Monitor performance in the wild, debug regressions, and iterate fast.

Required Skills:

1. 3+ years of hands-on ML experience with deep practical real-world experience in training models.
2. Strong Python and PyTorch fundamentals with exposure in distributed training, and modern fine-tuning techniques (LoRA, QLoRA, DPO, RLHF, etc.).
3. 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.
4. Rigorous about evaluation. You know that "looks good in a demo" is not a benchmark. You build the evals before you trust the model.
5. 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.
6. Bias toward shipping. You'd rather have a model running in production this week than a perfect one in a notebook next quarter.

Why Join

• Backed by YC, we’re on a mission to build a generational company out of India.
• Rocketship trajectory: We’re profitable, growing at YC speed, and handling 4M+ minutes of real conversations every week - you will have a shotgun seat in seeing these numbers multiply
• Founding team seat: You’ll be among the first 10 members and help shape our culture, GTM playbooks, and the very DNA of our growth story.
• Hard problems, real ownership: We’re orchestrating thousands of real-time Voice AI conversations in parallel. You’ll own high-stakes problems that touch engineering, customers, and revenue at once.
• Learn like a founder: This is not a narrow role. You’ll have visibility into GTM, product strategy, and customer feedback loops - and influence decisions beyond just code.
• Benefits: Competitive package + meaningful ESOP for early ownership + Health Insurance