Bolna provides an India-focused voice orchestration platform that lets businesses quickly build and deploy AI voice agents across multiple models and local languages.
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. Our team includes IIT alumni with experience at Bain, Atlassian, Uber, Zomato, and LinkedIn, and is backed by leading investors. 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. Preferred Skills: 1. Speech and real-time ML expertise: Experience working with speech, audio, multimodal, or real-time machine learning systems. 2. Voice AI domain knowledge: Hands-on experience with ASR, TTS, VAD, language identification, speaker systems, or conversational turn-taking. 3. Multilingual model development: Experience building and evaluating multilingual models, particularly for Indian languages. 4. Inference optimisation: Experience with streaming inference, latency optimisation, quantisation, distillation, or model compression for production deployment. WHY JOIN: - Backed to build big: Bolna is backed by Y Combinator and leading investors, and we are on a mission to build a generational voice AI company from 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 will be one of the earliest members of Bolna’s ML team and help shape our ML architecture, engineering culture, evaluation standards, and technical roadmap. - Hard problems, real ownership: We orchestrate thousands of real-time voice AI conversations in parallel. You will own high-stakes problems that directly affect engineering, customer experience, infrastructure cost, and revenue. - Learn like a founder: This is not a narrow role. You will have visibility into product strategy, customer feedback, and business outcomes—and influence decisions beyond just model development. - Benefits: Competitive package + meaningful ESOP for early ownership + Health Insurance