We’re looking for an ML Engineer (Applied Science) to train models for various realtime English conversational skills improvement use cases. Example projects include:
- Personalised english learning exercise recommendation system
- Build demographic specific ASRs sensitive to various accents,
- Empathy driven role play, similar to how an offline tutor would interact with a student,
- Training models for grammar/vocab/accentuated pronunciation and similar speech feedback metrics

The role involves experimenting with different training strategies, creating datasets, building task specific evals, beating our internal SOTA, deploying in production, and repeat
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At Stimuler, we’re building real-time conversational audio AI for English conversational skills improvement as a use case. We see our main competition as offline human English speaking tutors, so building things like empathy focused user experiences, student focused learning plans, and the likes - no longer remain good-to-have’s.



Our goal is to build the most effective way to learn how to speak English and have better conversations in real life, via a realtime UX.
We have a task-specific small model focused approach on our AI efforts so far. Our small models beat the best of frontier models on our specific tasks, and are a fraction of the total size
Desired experience:
- You have 2+ years of strong experience shipping ML models in production. This is an applied science role.
- You’re comfortable creating datasets from scratch, as well as building task specific evals from scratch.
- You should think in a customer-focused way, work in a tight-knit and cross-functional environment - being a team player and willing to take on whatever is best for the company
- Contribute to hiring as we expand
- Positive to have: Relevant experience working with NLP, or other speech specific models

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📌 ML Engineer, Applied Science (Bengaluru)
🏢 Stimuler
📍 Bengaluru