Principal ML - GenAI Engineer - Speech / Voice AI
About the role
Weave is seeking a Principal Engineer on the Machine Learning Team specialized in voice and audio modalities to design AI-powered features and build scalable ML infrastructure supporting 30,000+ healthcare practices. Leadership role focusing on MLOps, GenAI, and cross-team architectural coherence within Weave's data fellowship and ML platform initiatives.
Responsibilities
- Design and develop ML infrastructure, tooling, and models to help teams deliver world-class experiences
- Build internal and external products and platforms to enable teams to incorporate AI into their features and customer-facing products
- Translate product goals into actionable engineering plans and build scalable, resilient services for data integration and event processing
- Help product and development teams understand the data lifecycle and consult with teams on common ML patterns/tradeoffs
- Coach and collaborate inside and outside the team to elevate technical standards
- Write high-quality, performant, sustainable, and testable code while working in a cloud environment
- Monitor the industry landscape, anticipate where technological advances are heading, and ensure Weave stays ahead of the curve
- Cut through noise and hype to identify genuine strategic value; advocate for and lead key initiatives
- Shape company-wide standards for engineering excellence, observability, and reliability in distributed systems
- Actively mentor Staff and Senior Engineers across the fellowship, developing the next generation of technical leaders
- Elevate architectural thinking across teams through design reviews, documentation standards, and hands-on guidance
- Build organisational capability that persists beyond your individual contributions
Qualifications
- 12+ years of software engineering experience with progressive technical leadership scope
- Demonstrable experience building and deploying ML-driven B2B multi-tenant applications in production environments at scale for external products and customers
- Deep expertise in distributed systems architecture, including building and operating services that handle hundreds of millions of transactions and terabytes of data
- 15+ years of experience in Machine Learning or AI, with a focus on or expertise in audio and voice GenAI solutions at scale
- Deep expertise with modern ML tools and techniques such as LLMs, RAG, Prompt Engineering, Fine Tuning, and specifically high-scale audio/voice models and LLM evaluations
- Strong background in scalable data stores—both relational (PostgreSQL at scale, Vitess, Spanner) and NoSQL (Bigtable, Redis, etc.)
- Operational experience with cloud-native infrastructure on GCP or AWS, including Kubernetes, infrastructure-as-code, and highly available system design
- Track record of leading cross-team technical initiatives that delivered measurable business outcomes
- Demonstrated ability to influence without direct authority, build consensus across organisational boundaries, and translate technical tradeoffs into business terms
- Audio or Voice GenAI in Production at scale: Mandatory deep experience delivering meaningful voice/audio solutions to external products
- Background in compliance-heavy environments (healthcare, fintech) with experience navigating regulatory requirements in technical design
- History of external technical leadership: open source contributions, conference speaking, or published technical writing
Skills
Benefits
- Not explicitly listed in the provided description

About Weave
Customer communication and payments platform.
As the pace of innovation continues, it is growing more difficult to see the value of technology. Often meaningful information is inaccessible at the time it would be most beneficial. Weave threads together data, software and communication platforms to build stronger relationships at the point of contact by making valuable information instantly available in simple and intuitive formats. This delivers improved productivity, better collaboration and greater insights making it easier to meet the needs of patients and to build better business and clinical outcomes.
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