Senior ML - GenAI Engineer, Voice & Speech

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Senior ML - GenAI Engineer, Voice & Speech based in India.

This is an opportunity to build advanced machine learning infrastructure, models, and AI-powered products that operate at significant scale. You will work on emerging Generative AI, natural language, audio, and voice technologies while helping engineering teams integrate AI into customer-facing experiences. The role combines deep technical ownership with platform engineering, distributed systems, and close collaboration across product and development teams. You will help make sophisticated machine learning capabilities easier, safer, and more accessible for teams without requiring specialized research expertise. Your work will support systems handling hundreds of millions of people and large-scale datasets in production environments. You will join an autonomous, cross-functional team where experimentation, rapid prototyping, mentorship, and practical innovation are highly valued.

Accountabilities:

• Design and develop machine learning infrastructure, tooling, models, and platforms that enable teams to deliver high-quality AI-powered products.
• Build internal products and platforms that make it easier for engineering teams to incorporate AI and Generative AI capabilities into customer-facing features.
• Partner with product and engineering teams to explain machine learning data lifecycles, experimentation requirements, common patterns, anti-patterns, and technical tradeoffs.
• Consult with teams on end-to-end AI product development, helping them design effective and responsible customer experiences.
• Build scalable and resilient services supporting data integration, event processing, distributed workloads, and platform extensions.
• Contribute to product functionality capable of processing large amounts of data and traffic reliably and efficiently.
• Develop high-quality, performant, maintainable, sustainable, and testable code while taking ownership of engineering quality.
• Work across distributed cloud components and services to deliver robust machine learning solutions.
• Collaborate with stakeholders to translate product objectives into actionable engineering strategies and implementation plans.
• Develop and deploy machine learning models and pipelines using modern LLM, RAG, prompt engineering, fine-tuning, evaluation, and multimodal approaches.
• Build and operate low-latency natural language and real-time audio systems at scale, including transcription, ASR, interruption detection, audio alignment, and speech synthesis.
• Develop and maintain reliable libraries, SDKs, APIs, and abstractions for internal engineering teams.
• Work with large-scale datasets, including systems handling terabytes of data and hundreds of millions to billions of records.
• Coach and mentor engineers, share expertise, encourage best practices, and contribute to a collaborative technical culture.
• Explore emerging AI technologies and contribute to rapid prototyping and innovative solutions for evolving, open-ended problems.

Requirements:

• 5+ years of professional experience in Machine Learning or AI, preferably with a focus on natural language, plus strong software engineering and systems experience.
• Proven experience building and deploying ML-driven B2B, multi-tenant applications in production environments at significant scale.
• Experience managing and processing terabytes of data or hundreds of millions to billions of records.
• Strong programming skills in Python and experience with modern ML technologies and tooling such as Jupyter, Dagster, MLFlow, KubeFlow, DVC, Triton Server, LLMs, and Postgres.
• Hands-on experience with LLMs, RAG, prompt engineering, fine-tuning, LLM evaluation, and multimodal models.
• Experience with data labeling or annotation for audio or text-based machine learning use cases.
• Strong understanding of distributed systems and experience designing scalable, redundant, observable, and resilient services.
• Expertise in designing systems that operate across distributed datasets and services.
• Experience building and deploying solutions on public cloud platforms such as AWS or GCP.
• Strong engineering background with at least 3 years of experience in software engineering and systems, including coding and system design.
• Experience developing low-latency natural language models and pipelines at scale.
• Hands-on experience with real-time audio and voice technologies, including transcription, ASR pipelines, interruption detection, audio alignment, and speech synthesis.
• Familiarity with emerging AI technologies such as Model Context Protocol (MCP).
• Proficiency with containers, orchestration, and large-scale deployment patterns; experience with Kubernetes or GKE and the Operator Pattern is a plus.
• Experience working with highly sensitive data such as PHI/HIPAA and PII.
• Familiarity with automation and container-based workflow engines, GitOps, infrastructure as code, and configuration-driven systems.
• Experience creating clean abstractions, intuitive APIs, stable libraries, and reusable SDKs.
• Demonstrated ability to deliver complex projects on time in enterprise-grade production environments.
• Strong leadership, mentorship, collaboration, communication, and stakeholder-management skills.
• Self-driven mindset, strong bias for action, strategic thinking, technical curiosity, and a passion for execution.
• Bachelor's or equivalent advanced technical education in Computer Science, Machine Learning, Engineering, Data Science, or a related field is advantageous.
• A preference for open-source technologies, greenfield development, rapid prototyping, and solving ambiguous, continuously evolving problems.

Benefits:

• Fully remote opportunity based in India.
• Opportunity to work on advanced Generative AI, machine learning, voice, speech, and natural language technologies.
• Exposure to large-scale systems processing hundreds of millions of users and extensive datasets.
• Hands-on work with modern AI technologies including LLMs, RAG, multimodal models, fine-tuning, LLM evaluation, and real-time audio pipelines.
• Opportunity to influence how AI capabilities are integrated into customer-facing products and internal engineering platforms.
• High degree of autonomy within a cross-functional, self-empowered Agile environment.
• Collaboration with highly skilled engineers, product professionals, and technical stakeholders.
• Opportunities to mentor others and contribute to engineering standards, architecture, and technical strategy.
• Exposure to distributed cloud infrastructure, Kubernetes, workflow automation, observability, GitOps, and infrastructure-as-code practices.
• Opportunity to work in a greenfield environment with rapid prototyping and open-ended technical challenges.
• Strong focus on continuous learning, experimentation, innovation, and advancing practical AI capabilities.
• Flexible remote setup with an expectation to overlap India and U.S. business hours.