5 Speech Processing Jobs

We are looking for highly motivated and innovative Research Scientists to join our team in Bengaluru, with a focus on advancing multilingual, multicultural, and multimodal large language models (LLMs). Your primary responsibility will be to conduct cutting-edge research on Gemini, particularly in the multilingual, multicultural, and multimodal domain encompassing speech, vision, and text. This research has a direct path to impacting billions of users through Google products. This role provides a unique opportunity to contribute to foundational research in multilingual and multimodal LLMs, with a special emphasis on addressing unique challenges in the Asia-Pacific (APAC) region. You will collaborate with a world-class team at Google DeepMind globally. If you are passionate about shaping the future of human-computer interaction through multilingual and multimodal LLMs and are eager to make a significant impact on users in the APAC region and beyond, we encourage you to apply. Artificial Intelligence has the potential to be one of humanity's most valuable inventions. At Google DeepMind, we are a team of scientists, engineers, machine learning experts, and more, working together to advance the state of the art in artificial intelligence. We utilize our technologies for widespread public benefit and scientific discovery, collaborating with others on critical challenges while ensuring safety and ethics are our highest priorities. This position is within the Languages group at Google DeepMind India, where the focus is on all aspects of LLM development, making impactful contributions to enhance Gemini's multilingual performance. The group's work has also improved various Google products such as Gemini App, Assistant, Search, etc., including foundational contributions to Google Translate's expansion to 110 languages representing over 600 million speakers. As a Research Scientist at Google DeepMind, your key responsibilities will include: - Developing and evaluating multilingual, multicultural, and multimodal LLMs, designing, implementing, and evaluating capabilities in Gemini and other frontier models at Google. - Collaborating with a world-class team, working closely with other research scientists, engineers, and product teams across Google DeepMind to foster a collaborative and intellectually stimulating environment. - Contributing to real-world impact, seeing your work contribute to Gemini and other frontier models at Google with applications across various domains, directly influencing the future of Google products and services. - Contributing to the research community by sharing insights and participating in external academic workshops and conferences. The ideal candidate will possess a Ph.D. (or equivalent research experience) in Computer Science, Artificial Intelligence, or a related field, a strong publication record in top-tier AI conferences or journals, and a solid understanding of deep learning, natural language processing, computer vision, and/or speech processing. Experience with relevant ML frameworks such as JAX, TensorFlow, or PyTorch, along with excellent communication and collaboration skills, are essential. Additionally, experience with multilingual, multicultural, and/or multimodal learning in LLMs, pretraining, post-training techniques, prompt engineering, few-shot learning, and evaluations would be advantageous. Familiarity with large-scale model training and deployment, as well as strong programming skills in Python or similar languages, are also desired qualities in the ideal candidate.,

The Conversational AI team at Walmart is responsible for building and deploying core AI assistant experiences across Walmart, catering to millions of active users globally. As a Staff Data Scientist, you will play a crucial role in leading the evolution of the AI assistant platform by developing highly scalable Generative AI systems and infrastructure. This hands-on leadership position requires expertise in machine learning, ASR, large-scale distributed systems, multi-modal LLMs, and more. Your responsibilities will include partnering with key business stakeholders to drive the development and planning of proof of concepts and production AI solutions within the Conversational AI space. You will be involved in translating business requirements into strategies, initiatives, and projects aligned with business objectives. Designing, testing, and deploying cutting-edge AI solutions at scale to enhance customer experiences will be a key aspect of your role. Collaboration with applied scientists, ML engineers, software engineers, and product managers will be essential in developing the next generation of AI assistant experiences. Staying updated on industry trends in Generative AI, Speech/Video processing, and AI assistant architecture patterns will be crucial. Additionally, providing technical leadership, guidance, and mentorship to a skilled team of data scientists, as well as driving innovation through problem-solving cycles and research publication, are integral parts of this role. To qualify for this position, you should have a Master's degree with 8+ years or a Ph.D. with 6+ years of relevant experience in Computer Science, Statistics, Mathematics, or a related field. A strong track record in a data science tech lead role, extensive experience in designing and deploying AI products, and expertise in machine learning, NLP, speech processing, image processing, and deep learning models are required. Proficiency in industry tools and technologies, a deep interest in generative AI, and exceptional decision-making skills will be assets in this role. Furthermore, you should possess a thorough understanding of distributed technologies, public cloud platforms, and big data systems, along with experience working with geographically distributed teams. Business acumen, research acumen with publications in top-tier AI conferences, and strong programming skills in Python and Java are also essential qualifications for this position. Join the Conversational AI team at Walmart Global Tech, where you will have the opportunity to make a significant impact, innovate at scale, and shape the future of retail while working in a collaborative and inclusive environment.,

As a talented Full Stack Developer with expertise in Generative AI and Natural Language Processing, you will be a key member of our team, contributing to the design, development, and scaling of cutting-edge LLM and Generative AI applications to enhance user experiences. Your responsibilities will include developing backend logic and intelligent workflows using pre-trained AI models such as large language models (LLMs) and natural language understanding (NLU) engines. You will integrate and operationalise NLP and Generative AI models in production environments, including speech processing pipelines like automatic speech recognition (ASR) and text-to-speech (TTS) technologies. Applying techniques such as LLM fine-tuning, prompt engineering, and Retrieval-Augmented Generation (RAG) will be crucial for enhancing AI system performance. Moreover, you will design and deploy scalable full-stack solutions supporting AI-driven applications, working with various data sources to enable contextual AI retrieval and responses. Utilising cloud platforms like AWS/Azure effectively for hosting, managing, and scaling AI-enabled services will also be part of your role. If you are passionate about combining full-stack development with AI and LLM technologies to create innovative text and voice applications, we look forward to hearing from you. Qualifications: - 3+ years of hands-on experience in full-stack application development with a strong understanding of frontend and backend technologies. - 12 years of proven experience in designing and implementing AI-driven conversational systems. - Deep knowledge of integrating Speech-to-Text (STT) and Natural Language Processing (NLP) components into production-ready systems. Nice-to-Have Skills: - Exposure to MLOps practices, including model deployment, monitoring, lifecycle management, and performance optimization in production environments. What You'll Get: - Opportunity to work on one of the most advanced AI systems. - A high-performing, fast-paced startup culture with a deep tech focus.,

This role is ideal for an experienced engineer passionate about building high-performance, real-time audio processing systems. The ideal candidate will have hands-on experience in areas such as audio enhancement, restoration, forensic audio analysis.

What would you do? System Design: Architect and design end-to-end speech processing pipelines, from data acquisition to model deployment. Ensure systems are scalable, efficient, and maintainable. Advanced Modeling: Develop and implement advanced machine learning models for speech recognition, speaker diarization, and related tasks. Utilize state-of-the-art techniques such as deep learning, transfer learning, and ensemble methods. Research and Development: Conduct research to explore new methodologies and tools in the field of speech processing. Publish findings and present at industry conferences. Performance Optimization: Continuously monitor and optimize system performance, focusing on accuracy, latency, and resource utilization. Collaboration: Work closely with product management, data science, and software engineering teams to define project requirements and deliver innovative solutions. Customer Interaction: Engage with customers to understand their needs and provide tailored speech solutions. Assist in troubleshooting and optimizing deployed systems. Documentation and Standards: Establish and enforce best practices for code quality, documentation, and model management within the team. Required Skills 2+ years of experience in speech processing, machine learning, and model deployment. Demonstrated expertise in leading projects and teams. Technical skills: • Excellent knowledge in Python / Java programming. • In-depth knowledge of speech processing frameworks like, Wave2vec, Kaldi, HTK, DeepSpeech and Whisper. • Experience with NLP, STT, Speech to Speech LLMs and frameworks like Nvidia NEMO, PyAnnote. • Proficiency in Python and machine learning libraries such as TensorFlow, PyTorch, or Keras. • Experience with large-scale ASR systems, speaker recognition, and diarization algorithms. • Strong understanding of neural networks, sequence-to-sequence models, transformers and attention mechanisms. • Familiarity with NLP techniques and their integration with speech systems. • Expertise in deploying models on cloud platforms and optimizing for real-time applications. Good to have: • Experience with low-latency streaming ASR systems. • Knowledge of speech synthesis, STT (Speech-to-Text) and TTS (Text-to-Speech) systems. • Experience in multilingual and low-resource speech processing.