Staff ML - GenAI Engineer, Voice & Speech

Accountabilities:
Design, develop, and maintain scalable machine learning infrastructure, platforms, and production-grade AI models focused on voice, speech, and audio technologies. Build reusable internal tools, libraries, and services that enable engineering teams to efficiently integrate AI capabilities into customer-facing products. Partner with product managers, software engineers, and stakeholders to translate business objectives into robust machine learning solutions and engineering roadmaps. Provide technical leadership by advising teams on machine learning best practices, architectural decisions, experimentation strategies, and model lifecycle management. Develop resilient distributed systems that support large-scale data processing, event-driven architectures, and cloud-native AI workloads. Deliver high-quality, maintainable, and well-tested code while promoting engineering excellence through mentorship, collaboration, and technical guidance. Contribute to the evolution of AI platforms, ensuring scalability, observability, reliability, and responsible deployment of machine learning solutions. Stay at the forefront of emerging AI technologies and help drive innovation across voice, speech, and generative AI initiatives. Requirements 15+ years of experience in Machine Learning, Artificial Intelligence, or related engineering disciplines, including extensive experience building production-grade AI systems. Strong expertise in Generative AI technologies, including Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), prompt engineering, fine-tuning, multimodal models, and model evaluation techniques. Significant experience developing and deploying large-scale voice, speech, and audio machine learning solutions, including ASR, transcription, speech synthesis, and real-time audio processing. Proven experience building distributed systems capable of processing massive datasets and supporting enterprise-scale B2B applications. Advanced proficiency with Python and modern ML ecosystems, including tools such as MLFlow, Kubeflow, Dagster, DVC, Triton Server, Jupyter, PostgreSQL, and cloud platforms such as AWS or GCP. Strong understanding of cloud-native architectures, containerization, Kubernetes, infrastructure automation, and scalable software engineering practices. Experience working with data annotation, model training pipelines, experimentation frameworks, and production ML infrastructure. Excellent leadership, mentoring, communication, and stakeholder management skills with the ability to influence technical strategy across multiple teams. A proactive mindset, strong problem-solving abilities, and a passion for continuous learning and emerging AI technologies. Experience with technologies such as Model Context Protocol (MCP), GitOps, Infrastructure as Code, automation frameworks, low-latency AI pipelines, or highly regulated data environments is considered an advantage. Benefits Fully remote position based in India. Opportunity to work on cutting-edge Generative AI, voice, and speech technologies at enterprise scale. High-impact technical leadership role with significant influence on AI strategy and platform development. Collaborative, cross-functional engineering culture with strong ownership and autonomy. Exposure to modern cloud infrastructure, distributed systems, and large-scale machine learning platforms. Opportunities for mentorship, professional growth, and continuous technical learning. Flexible remote working environment with collaboration across India and US business hours.

How Jobgether works:
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