ML - GenAI Engineer, Voice & Speech

About this job

Weave is seeking a talented professional for the ML - GenAI Engineer, Voice & Speech position in India. You will become part of a collaborative machine learning group dedicated to helping developers easily build AI-driven applications that handle massive data sets. The team focuses on democratizing advanced tools so that cross-functional agile squads can safely launch cutting-edge features without needing a PhD. In your typical day, you will design and develop machine learning infrastructure, build internal platforms that incorporate artificial intelligence into customer-facing products, write high-performance code, and consult with various developers on best practices and data lifecycles. Working in a fully remote setup that overlaps India and US business hours, you will collaborate closely with product owners, backend and frontend developers, and devops personnel to shape how customers experience Weave's technological solutions.

Responsibilities

• Design and develop machine learning infrastructure, tooling, and models for team delivery.
• Help product and development teams understand data lifecycles and machine learning experimentation.
• Build internal platforms enabling teams to add AI into features and products.
• Consult with groups on machine learning patterns, anti-patterns, tradeoffs, and end-to-end experiences.
• Build scalable, resilient services supporting data integration and event processing.
• Write high-quality, performant, sustainable, and testable code.
• Coach and collaborate inside and outside the team to share expertise and best practices.
• Work in a cloud environment implementing functionality through distributed components.

Requirements

• 3-5 years of experience in Machine Learning or AI with a natural language focus.
• Experience moving and storing terabytes of data or hundreds of millions to billions of records.
• Experience building and deploying ML-driven B2B multi-tenant applications in production at scale.
• Familiarity with common ML technologies such as Python, Jupyter, workflow engines, DVC, Triton Server, LLMs, and Postgres.
• Experience with modern ML tools like RAG, prompt engineering, fine tuning, evaluations, and multi-modal models.
• Understanding of distributed systems and building scalable, redundant, and observable services.
• Experience building solutions to run on public clouds such as AWS or GCP.
• Demonstrated track record of delivering complex projects on time in enterprise environments.

Good to have

• Background with data analysis, visualization, and presentation.
• 3+ years of experience in engineering and systems with strong coding and system design proficiency.
• Experience with low latency natural language models and real-time audio models or speech synthesis.
• Proficient understanding of containers, orchestrators, Kubernetes, or GKE at scale.
• Experience with highly sensitive data such as PHI and PII.

Who should apply

This role suits experienced engineering professionals with a strong background in machine learning, artificial intelligence, and natural language processing who thrive in autonomous, cross-functional agile environments. Ideal candidates will have a history of managing massive datasets and building scalable production applications in the cloud. Because the position requires working closely with diverse stakeholders and mentoring peers, strong communication and collaboration skills are essential. This opportunity is not suitable for absolute freshers, as it specifically calls for several years of professional experience in the field.

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