3 Speech Ai Jobs

You are a highly experienced Lead Machine Learning Engineer specializing in Speech AI, Natural Language Processing (NLP), and Generative AI (GenAI). Your role is crucial in designing and expanding a production-grade speech-based virtual assistant powered by Large Language Models (LLMs), advanced audio signal processing, and multimodal intelligence. Collaborating closely with product, research, and DevOps teams, you will lead a group of ML engineers to create and implement cutting-edge AI solutions. In this role, your responsibilities include architecting and implementing advanced machine learning models for speech recognition (ASR), text-to-speech (TTS), NLP, and multimodal tasks. You will lead the development and fine-tuning of Transformer-based LLMs, including encoder-decoder architectures for audio and text tasks. Additionally, you will build custom audio-LLM interaction frameworks incorporating modality fusion, speech understanding, and language generation techniques. Your duties also involve designing and deploying LLM-powered virtual assistants with real-time speech interfaces for dialog, voice commands, and assistive technologies. You will integrate speech models with backend NLP pipelines to handle complex user intents, contextual understanding, and response generation effectively. Furthermore, you will design and implement end-to-end ML pipelines covering data ingestion, preprocessing, feature extraction, model training, evaluation, and deployment. Developing reproducible and scalable training pipelines using MLOps tools such as MLflow, Kubeflow, and Airflow with robust monitoring and model versioning will be part of your responsibilities. You will also drive CI/CD for ML workflows, model containerization (Docker), and orchestration using Kubernetes/serverless infrastructure. To stay updated with the latest advancements in Speech AI, LLMs, and GenAI, you will evaluate and drive the adoption of novel techniques. Experimenting with self-supervised learning, prompt tuning, parameter-efficient fine-tuning (PEFT), and zero-shot/multilingual speech models will be essential for innovation and progress. The required technical skills for this role include: - 10+ years of hands-on experience in machine learning, with a deep focus on audio (speech) and NLP applications. - Expertise in Automatic Speech Recognition (ASR) and Text-to-Speech (TTS) systems, including tools like Wav2Vec, Whisper, Tacotron, FastSpeech, etc. - Strong knowledge of Transformer architectures like BERT, GPT, T5, and encoder-decoder LLM variants, including training/fine-tuning at scale. - Proficiency in Python programming and deep learning frameworks like PyTorch and TensorFlow. - In-depth understanding of audio signal processing concepts such as MFCCs, spectrograms, wavelets, sampling, filtering, etc. - Experience with multimodal machine learning, including the fusion of speech, text, and contextual signals. - Deployment of ML services with Docker, Kubernetes, and experience with distributed training setups on GPU clusters or cloud platforms (AWS, GCP, Azure). - Proven experience in building production-grade MLOps frameworks and maintaining model lifecycle management. - Experience with real-time inference, latency optimization, and efficient decoding techniques for audio/NLP systems. Preferred qualifications for this role include: - Master's or Ph.D. in Computer Science, Machine Learning, Signal Processing, or related technical discipline. - Publications or open-source contributions in speech, NLP, or GenAI. - Familiarity with LLM alignment techniques, RLHF, prompt engineering, and fine-tuning using LoRA, QLoRA, or adapters. - Previous experience in deploying voice-based conversational AI products at scale.,

As a part of this esteemed organization in the Insurance Industry, your role will revolve around evangelizing and continuously working towards enhancing the organizational understanding of AI/ML capabilities. You will collaborate with senior leadership to strategically propose the use of AI/ML to improve business outcomes. By partnering with functional heads, you will address and resolve business challenges by leveraging AI & Analytics solutions effectively. Your responsibilities will include translating business problems into analytical challenges and implementing AI/ML techniques to drive end-to-end strategic initiatives. You will play a key role in scaling the AI/ML agenda through the development of various solutions. Additionally, you will empower business decision-making by presenting data-driven insights to top leaders through compelling storytelling. Building and sustaining external relationships with academia forums and industry partners will be crucial to gain new perspectives and innovative approaches. You will lead AI & Analytics projects comprehensively, from conceptualization to continuous monitoring, ensuring successful implementation. Key competencies and skills essential for this role include being a strong collaborator with the ability to influence conventional thinking, possessing analytical thinking skills, and effectively presenting insights to business leaders. Your hands-on experience with Analytics/ML technologies, open-source tools like Python and R, and deploying AI/ML solutions in a cloud environment will be highly valuable. Success in this role will be measured by your ability to form partnerships with functional leaders, improve operational efficiencies, execute organization-wide initiatives, and implement AI/ML use cases effectively. It will also depend on managing team engagement and talent pipeline while ensuring algorithm outcomes meet expectations consistently. You will interact with internal stakeholders like CXOs, senior leadership, and external partners from academia forums and cross-industries. An MBA or masters degree in quantitative fields from reputable institutes, along with a minimum of 12-15 years of analytical work experience, will be preferred for this role.,

As an experienced professional in the field of SaaS, AI, or enterprise software inside sales, you will be responsible for designing and executing multi-touch email and calling sequences targeted towards industry verticals such as EdTech, Studios, Call Centers, and Healthcare. Your role will involve generating and qualifying leads by utilizing lead scoring metrics to identify high-intent prospects. Additionally, you will collaborate with technical team members to schedule and conduct virtual product demos. Maintaining CRM hygiene, managing follow-up cadences, and documenting sales conversations will be crucial aspects of your day-to-day responsibilities. You will also play a key role in proposal creation, engaging in commercial negotiation over email, and preparing necessary documentation to support the sales process. The ideal candidate should possess at least 3 years of experience in SaaS, AI, or enterprise software inside sales and demonstrate excellent written and verbal communication skills. Familiarity with CRMs such as HubSpot and Zoho, email automation tools like Lemlist and Apollo.io, and outreach cadences is essential. An understanding of speech AI, SaaS pricing, and B2B buyer journeys would be advantageous. Moreover, you should exhibit a strong ability to handle rejection, follow up persistently, and independently close small-to-mid deals. Over the first 36 months in this role, your performance goals will include qualifying and nurturing a lead pipeline comprising a minimum of 100 active accounts. You will be expected to schedule at least 15 qualified product demos with relevant decision-makers and contribute to the closure of 2 SaaS contracts or 1 custom services engagement.,