Job Title

AI Engineer - Speech Modelling & Quality (STT / TTS)Location: Bangalore/Mumbai/Hyderabad/Gurgaon/IndoreWork from OfficeRole OverviewThe Speech Modelling & Quality Senior Engineer is responsible for end-to-end ownership ofspeech quality delivered by the Indic Speech AI platform. This role directly determines howaccurately speech is recognized and how natural, intelligible, and expressive synthesizedspeech sounds across all supported Indic languages.This role exists to ensure that improvements in model capability translate into measurable,sustained gains in real-world user experience, and that quality does not regress as theplatform scales, new languages are added, or models are upgraded.This role owns outcome-level quality, not just model execution.Core ResponsibilitiesThe role defines and owns quality metrics for speech-to-text and text-to-speech systems,including word error rate, substitution and deletion patterns, punctuation accuracy,pronunciation correctness, prosody, intelligibility, and naturalness.The role performs deep error analysis across languages, accents, acoustic conditions,device types, and usage contexts to identify systematic weaknesses in speech recognitionand synthesis.The role drives language-specific optimization strategies, ensuring that each Indic languageis tuned independently and not treated as a secondary outcome of multilingual training.The role collaborates with ML engineering and training teams to define data requirements,sampling strategies, and curriculum approaches required to improve quality.The role ensures that improvements in one language or model dimension do not introduceregressions in others, enforcing strict quality isolation and regression testing.The role validates that training gains are preserved through inference, ensuring no qualityloss due to quantization, batching, streaming, or runtime optimizations.Operational OwnershipThe Speech Modelling & Quality Lead owns quality regressions in production. If recognitionaccuracy drops, synthesized speech quality degrades, or users experience noticeabledeterioration, this role is accountable.The role owns the pre- and post-release quality validation process, including baselinecomparisons, A/B evaluations, and rollout gating criteria.The role is responsible for ensuring that model upgrades, retraining, or data changes do notnegatively impact user-facing quality metrics.The role participates in incident analysis when customer complaints, usage drop-offs, ormonetization anomalies are traced back to speech quality issues.Key InterfacesThis role works closely with the PyTorch & Python ML Engineering Lead to translate qualityfindings into concrete model changes.The role interfaces with the PyTorch Lightning Training Lead to ensure training strategiesalign with quality improvement goals.The role collaborates with the GPU Inference Optimization Lead to ensure inferenceoptimizations do not compromise quality.The role works with Language Guardrails teams to ensure safety mechanisms do not distortor degrade speech output unintentionally.The role coordinates with Monetization Analytics & Billing teams when quality changescorrelate with usage or revenue shifts.Explicit Non-ResponsibilitiesThis role does not own training infrastructure, GPU scheduling, or Kubernetes operations.This role does not own raw ML pipeline implementation or inference service engineering.This role does not define system architecture or networking Behaviour.Role ExpectationThe Speech Modelling & Quality Lead is expected to operate with a user-centric andlanguage-centric mindset, treating speech quality as the primary product outcome.Success in this role is measured by: Sustained reduction in word error rates Improved naturalness and intelligibility of synthesized speech Language-specific quality leadership rather than averaged performance Absence of silent quality regressions in productionClear correlation between quality improvements and user adoption or retention