Founding ML Engineer

Role Overview

At Bolna, we’re building tools that change the way teams leverage Voice AI. We’re looking for a Founding Machine Learning Engineer to own the end-to-end lifecycle of building, evaluating, deploying, and improving models that power millions of production conversations. This is a high-impact, high ownership role where you won’t just work on Bolna’s ML stack—you’ll help build the foundation it scales on.

Responsibilities

• Build the data engine - Design pipelines to source and clean conversational voice data across Indian languages, accents, and telephony conditions.
• Fine-tune models that ship - Fine tune and train models to improve accuracy, speed, and reliability across different use-cases.
• Define what "good" means - Build evaluation datasets and benchmarks for transcription accuracy, voice naturalness, interruption handling, latency, and end-to-end conversation quality.
• Ship to production - Work with the engineering team to deploy models into a latency-sensitive, high-volume system.

Requirements

• 3+ years of hands-on ML experience with deep practical real-world experience in training models.
• Strong Python and PyTorch fundamentals with exposure to distributed training and modern fine-tuning techniques (LoRA, QLoRA, DPO, RLHF, etc.).
• Experience designing data pipelines from collection, cleaning, labeling, deduplication, and augmentation.
• Rigorous approach to evaluation and building benchmarks.
• Bias toward shipping and production-ready models.

Nice to Have

• Speech model experience with real-time / streaming inference.
• Experience with latency optimization, quantization, and distillation.
• Voice AI domain knowledge (ASR, TTS, VAD, language identification).
• Multilingual model development, particularly for Indian languages.

Benefits

• Competitive package
• Meaningful ESOP for early ownership
• Health Insurance

Skills

• Python
• PyTorch
• LoRA/QLoRA
• ASR/TTS
• Machine Learning