Senior ML - GenAI Engineer, Voice & Speech

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.