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Open nowPosted 632 days ago

ML Engineer, Applied Science

Stimuler6 open roles

Where
India
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Your applicationOpen nowML Engineer, Applied ScienceStimuler · India

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11.8% of postings close within 7 days. Measured by our own scanner across the market.

Share of postings closed within
  1. 2.1%1 day
  2. 4.4%3 days
  3. 11.8%7 days
  4. 18.6%14 days
  5. 35.6%30 days
  6. 45.1%60 days
This job: posted 632 days ago

The posting

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
  • Good to have: Relevant experience working with NLP, or other speech specific models

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