Were seeking a highly skilled Data Scientist with deep expertise in speech technologies,
advanced NLP, and LLM fine-tuning to join our growing AI research team. In this role, youll
develop and optimize cutting-edge machine learning systems that power intelligent audio and
language-based solutions. Youll play a key role in creating next-generation AI products that
emphasize privacy, performance, and scalability.
Key Responsibilities
Build a real-time voice-to-text (ASR) pipeline using models like Whisper, wav2vec2, or
custom speech models.
Design and implement intent detection and entity extraction logic based on transcribed
speech, keywords, and semantic patterns.
Fine-tune LLMs and transformer models (e.g., BERT, RoBERTa) for downstream tasks
such as entity recognition, intent classification, and contextual understanding.
Optimize the full model pipeline for low-latency mobile inference using TFLite, ONNX,
and quantization techniques.
Collaborate closely with AI Product and MLOps teams for deployment, feedback-driven
iteration, and continuous performance monitoring.
Required Technical Skills
Proven experience with ASR models like Whisper, wav2vec2, DeepSpeech, Kaldi, or
Silero, including fine-tuning for Indian accents and multilingual speech.
Deep understanding of NLP techniques, including keyword spotting, masked token
decoding, sequence labeling, and pattern-based classification.
Proficient in fine-tuning LLMs and BERT-like architectures for intent detection, NER, and
domain adaptation.
Ability to extract, manipulate, and analyze speech metadata for feature engineering and
signal enrichment.
Strong hands-on skills with model optimization techniques like quantization-aware
training (QAT), pruning, and runtime-efficient deployment (e.g., on-device inference).
Excellent programming skills in Python, with strong command over PyTorch or
TensorFlow, and familiarity with NumPy, pandas, and real-time processing tools.
Qualifications
Bachelors or Masters degree in Computer Science, Electrical Engineering, Data
Science, or a related technical field.
Academic or practical background in speech processing, ASR, telecom analytics, or
applied NLP is highly preferred.
Strong portfolio of real-world speech/NLP applications, open-source contributions, or
peer-reviewed research.
Experience
3 to 6+ years of hands-on experience in speech AI, NLP for intent detection, or machine
learning model development.
Demonstrated success in building, deploying, and optimizing ML models for real-time,
low-latency use cases.
Contributions to notable open-source projects such as openai/whisper,
mozilla/DeepSpeech, or facebook/wav2vec2
Job Classification
Industry: FinTech / PaymentsFunctional Area / Department: Data Science & AnalyticsRole Category: Data Science & Machine LearningRole: Data ScientistEmployement Type: Full time