Speech Recognition Engineer | Voice Technology Specialist

🎙️ We’re Hiring: Speech Recognition Engineer | Voice Technology Specialist🕒 Employment Type: Full-Time💼 Level: Mid-Level to SeniorWe are seeking a technically skilled and innovative Speech Recognition Engineer | Voice Technology Specialist to develop, optimize, and deploy speech recognition systems and voice-enabled technologies. This role combines automatic speech recognition (ASR), speech processing, machine learning, natural language processing, and voice application engineering to deliver accurate, responsive, and reliable voice experiences across multiple platforms and use cases.🎯 Key Responsibilities

• Design, develop, test, and maintain speech recognition systems and voice-processing applications.
• Build and optimize automatic speech recognition (ASR) models for converting spoken language into accurate text.
• Develop speech-processing pipelines for audio capture, preprocessing, feature extraction, recognition, and post-processing.
• Apply machine learning and deep learning techniques to improve speech recognition accuracy and robustness.
• Work with acoustic models, language models, speech representations, and decoding algorithms.
• Process and analyze audio datasets to support model training, evaluation, and performance improvement.
• Develop solutions for noise reduction, voice activity detection, speaker segmentation, and audio enhancement.
• Improve speech recognition performance across different accents, dialects, speaking styles, and acoustic environments.
• Evaluate speech recognition accuracy using metrics such as word error rate (WER), character error rate (CER), and other relevant measures.
• Identify and resolve recognition errors, pronunciation variations, background-noise interference, and transcription inconsistencies.
• Develop and optimize speech-processing algorithms for real-time and batch-processing applications.
• Integrate speech recognition capabilities into mobile applications, web platforms, enterprise systems, and voice-enabled products.
• Implement voice interfaces for virtual assistants, conversational applications, customer-service solutions, and accessibility tools.
• Integrate speech-to-text, text-to-speech, and related voice technologies where required.
• Work with NLP engineers to improve transcription post-processing, punctuation restoration, text normalization, and language understanding.
• Develop multilingual and domain-specific speech recognition solutions where applicable.
• Evaluate third-party speech APIs, cloud speech services, and open-source speech recognition frameworks.
• Build automated testing and benchmarking pipelines for evaluating speech model performance.
• Conduct experiments to compare model architectures, training strategies, datasets, and inference configurations.
• Optimize model latency, computational efficiency, memory usage, and deployment performance.
• Support deployment of speech models on cloud infrastructure, servers, mobile devices, and edge computing platforms.
• Collaborate with data scientists, ML engineers, software developers, product managers, and UX specialists.
• Maintain reliable data pipelines for audio collection, labeling, preprocessing, augmentation, and quality assurance.
• Ensure speech datasets are appropriately managed, documented, and handled in accordance with privacy requirements.
• Monitor deployed speech recognition systems and investigate performance degradation or production incidents.
• Support model retraining, version management, continuous evaluation, and ongoing performance improvements.
• Research emerging speech AI technologies, transformer-based architectures, foundation models, and multilingual speech systems.
• Develop technical documentation covering model architecture, evaluation methods, deployment processes, and system performance.
• Contribute to voice technology roadmaps, technical design reviews, and product innovation initiatives.
• Recommend improvements to speech recognition accuracy, scalability, reliability, and user experience.✅ Requirements
• Bachelor’s or Master’s degree in Computer Science, Electrical Engineering, Computer Engineering, Artificial Intelligence, Speech Technology, or a related field.
• Proven experience in speech recognition, audio processing, machine learning, voice technology, or a related discipline.
• Strong programming skills in Python, C++, or other relevant programming languages.
• Solid understanding of machine learning, deep learning, neural networks, and statistical modeling.
• Experience with automatic speech recognition systems and speech-processing workflows.
• Familiarity with speech recognition frameworks such as Whisper, Kaldi, ESPnet, NeMo, or equivalent technologies.
• Experience with deep learning frameworks such as PyTorch or TensorFlow.
• Understanding of acoustic modeling, language modeling, tokenization, decoding, and speech feature extraction.
• Familiarity with audio representations such as spectrograms, Mel-frequency cepstral coefficients (MFCCs), and log-Mel features.
• Experience evaluating speech recognition performance using WER, CER, and other relevant metrics.
• Knowledge of audio preprocessing, noise reduction, voice activity detection, and audio segmentation.
• Understanding of natural language processing and language-model integration is advantageous.
• Experience working with multilingual, accented, noisy, or domain-specific speech data is beneficial.
• Familiarity with transformer architectures and self-supervised speech models is preferred.
• Experience with audio data preparation, annotation, augmentation, and dataset quality assessment.
• Knowledge of model optimization, quantization, inference acceleration, and deployment techniques is advantageous.
• Familiarity with cloud platforms, APIs, Docker, and production deployment workflows is beneficial.
• Understanding of real-time audio processing and streaming architectures is an advantage.
• Strong analytical and problem-solving skills.
• Excellent debugging, experimentation, and performance-evaluation abilities.
• Ability to interpret experimental results and make data-driven technical decisions.
• Strong communication and technical documentation skills.
• Ability to collaborate with cross-functional engineering, research, and product teams.
• Strong attention to detail and commitment to model accuracy and system reliability.
• Ability to manage multiple development tasks and meet project deadlines.
• Familiarity with speech privacy, secure audio-data handling, and responsible AI practices is beneficial.
• Relevant certifications or specialized training in AI, machine learning, speech processing, or cloud technologies are advantageous.🌟 What We Offer
• Competitive salary and comprehensive employee benefits.
• Opportunity to work on advanced speech AI and voice-enabled technologies.
• Exposure to modern speech recognition models, deep learning frameworks, and audio-processing tools.
• Professional development in speech processing, machine learning, NLP, and AI engineering.
• Training and support for relevant technical certifications.
• Opportunities to develop multilingual voice applications and real-time speech solutions.
• Collaboration with experienced AI engineers, researchers, software developers, and product teams.
• Opportunities to contribute to innovative voice assistants, conversational AI, and accessibility solutions.
• Access to modern development tools, cloud infrastructure, and machine learning platforms.
• Recognition for technical innovation and improvements in speech recognition performance.
• Career progression toward Senior Speech Recognition Engineer, Speech AI Lead, Voice Technology Architect, Machine Learning Manager, or Head of Speech Technology.