AI Engineer – ASR

• Lead development and deployment of speech recognition systems for automated reading assessment across multiple languages
• Supervise speech data collection, annotation, data preparation, and model training
• Manage decoding, alignment, error analysis, and deployment across the ASR pipeline
• Provide technical input on speech data collection design across languages, dialects, age groups, reading levels, environments, devices, and target items
• Define annotation guidelines and quality checks for transcripts, reading errors, disfluencies, background speech, and related phenomena
• Identify data gaps and annotation inconsistencies through model error analysis
• Recommend targeted data collection or re-annotation
• Design annotation schemas and inter-annotator quality processes
• Train, fine-tune, and evaluate ASR models for children’s read speech across languages and accents
• Build audio preprocessing, segmentation, normalization, transcription alignment, and model training pipelines
• Adapt ASR architectures including Whisper, wav2vec 2.0, Conformer, CTC/RNN-T, or similar models
• Optimize models for low-bandwidth, store-and-forward, server-based, offline, and mobile inference
• Detect substitutions, omissions, insertions, repetitions, partial-word attempts, hesitations, and self-corrections
• Implement forced alignment, phoneme-level alignment, or pronunciation-scoring approaches
• Conduct systematic error analysis by language, reading level, age, accent, gender, recording conditions, and device
• Collaborate with assessment experts and field teams to translate model outputs into reading accuracy, WCPM, fluency, and reading-level measures
• Define and track ASR metrics including WER/CER, word-level accuracy, error-detection precision/recall, alignment accuracy, and agreement with human evaluators
• Build reproducible experimentation and model-evaluation pipelines
• Maintain clear technical documentation

• A Degree in any Mathematics/Computer Science/Data Science or related STEM field
• 3–5 years of full-time experience, including at least 2 years in an AI/ML role
• Strong experience in automatic speech recognition, speech processing, or spoken-language technologies
• Strong Python skills
• Experience with PyTorch or similar deep-learning frameworks
• Experience with modern ASR architectures and toolkits such as Hugging Face Transformers, NeMo, Kaldi, or equivalent
• Understanding of acoustic modelling
• Understanding of CTC, transducer, and encoder-decoder architectures
• Understanding of decoding and beam search
• Understanding of language models
• Understanding of forced alignment
• Understanding of phoneme representations
• Understanding of WER/CER and ASR error analysis
• Experience preparing and working with large-scale audio and transcription datasets
• Ability to diagnose model errors systematically
• Candidates based anywhere in India

• Impact at a global scale supporting millions of children
• Opportunity to build Digital Public Goods for the Global South
• Autonomy to experiment with latest SOTA models
• Support from a 5-year strategic roadmap and funding from partners including the Gates Foundation and Anthropic
• Work alongside a global team of experts
• Flexible, remote-first work environment
• Work from anywhere in India
• Opportunity to travel periodically to field locations
• Competitive remuneration benchmarked against industry standards and commensurate with experience
• Equal opportunity workplace
• Full-time employment