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Urgent! Speech Data Scientist - Machine Learning Job Opening In Bengaluru – Now Hiring Albatronix Consulting Private Limited

Speech Data Scientist Machine Learning



Job description

<p><p><b>About The Opportunity : </b></p><br/><p>Join a high-velocity engineering team building robust, low-latency speech and voice solutions for large-scale deployments.</p><br/><p>You will design and ship state-of-the-art ASR models and production pipelinesbridging classical signal-processing foundations with modern transformer-based speech models to drive measurable product impact.</p><br/><p><b>Role & Responsibilities : </b></p><br/><p>- Lead design, training and optimisation of ASR systemsend-to-end and hybridusing transformer and sequence modeling (Wav2Vec 2.0, Whisper, CTC, attention-based encoders/decoders).</p><br/><p>- Develop and evaluate speech pre-processing and DSP pipelines (feature extraction, augmentation, denoising, VAD) to improve robustness across noisy, multilingual inputs.</p><br/><p>- Prototype and productionise model-serving solutions : containerised inference, latency optimisation, batching, and autoscaling for cloud and edge deployments.</p><br/><p>- Collaborate with data engineers and linguists to curate datasets, define annotation guidelines, and run rigorous evaluation (WER, CER, streaming metrics) and error-analysis cycles.</p><br/><p>- Implement reproducible training workflows, CI/CD for models, monitoring for drift and performance, and automation for retraining and A/B evaluation.</p><br/><p>- Mentor peers, author engineering-excellence patterns (testing, observability), and present technical results to product and stakeholder teams.</p><br/><p><b>Skills & Qualifications : </b></p><br/><p><b>Must-Have : </b></p><br/><p>- 5+ years in speech recognition or related audio ML roles with proven production impact.</p><br/><p>- Strong DSP and audio analysis fundamentals (feature engineering, spectrograms, filtering, VAD).</p><br/><p>- Hands-on experience with PyTorch and/or TensorFlow for building and training ASR models.</p><br/><p>- Practical knowledge of transformer-based speech models (Wav2Vec 2.0, Whisper) and sequence losses (CTC), plus RNN/CNN architectures.</p><br/><p>- Proficient in Python; experience with C++/Java for production deployments is highly desirable.</p><br/><p>- Experience deploying models in cloud environments (AWS/GCP) and container orchestration (Docker/Kubernetes); familiar with MLOps tooling and CI/CD.</p><br/><p><b>Preferred : </b></p><br/><p>- Background in multilingual ASR, low-resource languages, or on-device/edge inference optimisation.</p><br/><p>- Experience with large-scale data pipelines, annotation platforms, and semi-supervised / self-supervised learning workflows.</p><br/><p>- Familiarity with production monitoring (prometheus/grafana), model explainability, and privacy-preserving ML techniques.</p><br/><p><b>Benefits & Culture Highlights : </b></p><br/><p>- High-autonomy engineering culture with strong emphasis on ownership, mentorship, and career growth.</p><br/><p>- Opportunity to influence product direction and work on state-of-the-art speech models at scale.</p><br/><p>- Competitive compensation, flexible hybrid work, and learning budget for conferences and training.</p><br/><p>We are seeking a results-oriented Speech Scientist who thrives on technical ownership and delivering dependable voice AI in real-world settings.</p><br/><p>Apply if you want to push ASR boundaries and build production-grade speech systems that scale.</p><br/></p> (ref:hirist.tech)


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