TTS Jobs in Bengaluru

Machine Learning Engineer - Speech AI (ASR & TTS) Location: Bengaluru, Karnataka, India (On-Site) Department: Engineering Employment Type: Full-Time About Sarvam.ai Sarvam.ai is a pioneering generative AI startup headquartered in Bengaluru, India. We specialize in leading transformative research and development in speech and language technologies. Focused on building state-of-the-art ASR (Automatic Speech Recognition) and TTS (Text-to-Speech) models, particularly for Indic languages, we aim to redefine human-computer interaction with cutting-edge, AI-driven solutions. Join us as we push the boundaries of Speech AI to create inclusive, scalable, and intelligent voice-based applications for diverse communities worldwide. Role Overview We are seeking an experienced Machine Learning Engineer specializing in Speech AI (ASR & TTS). The ideal candidate will work on deep learning-based ASR and TTS models, improving accuracy, efficiency, and multilingual capabilities while deploying them at scale. The role involves developing and optimizing speech recognition and synthesis models with a focus on low-resource languages, real-time inference, and scalability. If you have a passion for speech processing and deep learning, this is a great opportunity to make a significant impact in a rapidly growing field. Key Responsibilities ASR (Automatic Speech Recognition) Develop, train, and optimize speech-to-text models using state-of-the-art architectures like Wav2Vec, Whisper, Conformer, and DeepSpeech. Implement techniques for low-latency ASR inference, including beam search, language model integration, and real-time transcription. Improve speech recognition accuracy for low-resource languages, especially Indic languages, using transfer learning and data augmentation. Optimize ASR pipelines for noise robustness, speaker adaptation, and domain-specific transcription. TTS (Text-to-Speech) Develop and fine-tune neural TTS models such as Tacotron, FastSpeech, VITS, or WaveNet for high-quality, natural-sounding speech synthesis. Implement multilingual and expressive TTS models with prosody and emotion control. Optimize TTS inference for deployment on edge devices, mobile, and cloud platforms. Improve speech synthesis quality through voice cloning, neural vocoders (HiFi-GAN, WaveGlow), and prosody modeling. General Speech AI Responsibilities Benchmark and profile ASR/TTS models to improve latency, efficiency, and deployment performance. Deploy scalable speech AI APIs on AWS, Azure, or GCP for real-world applications. Optimize ASR & TTS models for edge and offline inference. Stay updated with the latest advancements in speech AI, neural vocoders, and real-time inference techniques. Must-Have Qualifications Experience: 2-3 years of experience in speech AI, deep learning, or machine learning, with a focus on ASR & TTS. Education: Bachelor s or Master s degree in Computer Science, AI/ML, Speech Processing, or a related field. ML Frameworks: Proficiency in PyTorch or TensorFlow for training and deploying ASR/TTS models. ASR Expertise: Experience with speech-to-text architectures like Whisper, Wav2Vec, Conformer, or DeepSpeech. TTS Expertise: Experience with speech synthesis models like Tacotron, FastSpeech, or VITS. Speech Signal Processing: Understanding of MFCCs, STFT, phonemes, prosody modeling, and feature extraction. Inference Optimization: Hands-on experience with TensorRT, ONNX, or quantization (INT8, FP16) for ASR/TTS. Cloud & Edge Deployment: Experience deploying speech models on AWS, GCP, or Azure. Preferred Qualifications Experience with speech diarization, speaker recognition, or language modeling for ASR. Familiarity with zero-shot TTS, voice cloning, and multilingual speech modeling. Understanding of CUDA optimization and low-bit quantization for ASR/TTS models. Contributions to open-source speech AI projects or a strong GitHub portfolio showcasing relevant work. Experience with real-time streaming ASR/TTS applications and low-latency inference. Innovative Impact: Work on AI-driven speech solutions that are changing how people interact with technology, especially in low-resource languages. Cutting-Edge Technology: Contribute to the development of state-of-the-art speech AI models in a rapidly advancing field. Collaborative Environment: Work with a team of experts in AI, machine learning, and speech processing, in a startup culture. Growth Opportunities: Sarvam.ai offers exciting career growth in a fast-paced environment with opportunities for personal and professional development. Interested candidates are invited to submit their resume, cover letter, and any relevant project portfolios or GitHub links showcasing their experience in ASR, TTS, or Speech AI. Strong AI-related projects, whether in industry, research, or personal work, will be highly valued. Qualification : Bachelors or Masters degree in Computer Science, AI/ML, Speech Processing, or a related field.

Software Engineer III - AI/ML, Platforms and Devices Company: Google Location: Bengaluru, Karnataka, India Minimum Qualifications: Bachelor s degree or equivalent practical experience. 2 years of experience in software development with one or more programming languages, or 1 year with an advanced degree. 2 years of experience in data structures or algorithms. 1 year of experience in one or more of the following: Speech/audio (e.g., technology duplicating and responding to the human voice), reinforcement learning (e.g., sequential decision making), ML infrastructure, or specialization in another ML field. 1 year of experience with ML infrastructure (e.g., model deployment, model evaluation, optimization, data processing, debugging). Preferred Qualifications: Master's degree or PhD in Computer Science or a related technical field. Experience developing accessible technologies. About the Job Google's software engineers work on cutting-edge technologies that transform how billions of users connect, explore, and interact with information. Our products must handle data at a massive scale, far beyond web search. We seek engineers who bring innovative ideas from various fields, including information retrieval, distributed computing, large-scale system design, networking, data storage, security, artificial intelligence (AI), natural language processing (NLP), UI design, and mobile development. As a Software Engineer, you will work on training and optimizing complex machine learning (ML) models for the Tensor Processing Unit (TPU). By enabling models across diverse applications like camera, speech, Translate, TTS (Text-to-Speech), and others on Edge TPU, you will gain valuable experience in efficient model architectures, optimization techniques, and on-device machine learning at Google. You will also be responsible for managing project priorities, deadlines, and deliverables. Google's mission is to organize the world s information and make it universally accessible and useful. Our Devices & Services team combines the best of Google AI, software, and hardware to create radically helpful experiences for users. We design and develop new technologies and hardware to make user interactions faster, more seamless, and powerful. Whether advancing form factors, improving interaction methods, or innovating new ways to capture and sense the world around us, our Devices & Services team is helping make people's lives better through technology. Responsibilities Write product or system development code. Collaborate with peers and stakeholders through design and code reviews to ensure best practices (e.g., style guidelines, accuracy, testability, and efficiency). Contribute to documentation or educational content and adapt based on product updates and user feedback. Triage product or system issues, debug, track, and resolve by analyzing the source of issues and their impact on hardware, network, or service operations. Implement solutions in one or more specialized Machine Learning (ML) areas, utilize ML infrastructure, and contribute to model optimization and data processing. Qualification : Master's degree or PhD in Computer Science or a related technical field.