The Role
The Machine Learning Engineer will manage the full lifecycle of model deployment, enhance model accuracy and performance, and design data pipelines for voice AI applications.
Summary Generated by Built In
At Bolna, we’re building tools that change the way teams leverage Voice AI.
We’re looking for a Machine Learning Engineer who will own the full lifecycle of shipping models into a production system handling millions of conversations a day.
This is an early, high-impact role where you’ll shape the foundation of our product and directly influence its reliability, scalability, and performance.
Our team is composed of IIT alums having worked at Bain, Atlassian, Zomato and are backed by top investors.
- 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. Set up human-in-the-loop pipelines to capture subjective quality at scale.
- 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.
- 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.
- 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
Skills Required
- 3+ years of hands-on ML experience
- Strong Python and PyTorch fundamentals
- Experience designing data pipelines
- Experience with speech models is a plus
- Real-time/streaming inference experience
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The Company
What We Do
Bolna is a Voice AI Platform purpose-built for India’s scale, linguistic complexity, and cost sensitivity. We enable enterprises to go live with thousands of concurrent calls in days, not months.
