Staff Machine Learning Engineer, Gen AI | Voice & Speech

About the role

Weave is seeking a Staff Machine Learning Engineer focused on voice and speech within our specialized Machine Learning Team, where you will drive product innovation and build AI-powered applications that redefine industry standards. In this capacity, you will own the design of systems that empower cross-functional teams to integrate sophisticated AI capabilities seamlessly into their workflows and customer interactions. You will act as a critical technical authority, bridging advanced machine learning methodologies with the pragmatic demands of real-world deployment in the healthcare sector. Your work will directly support over 30,000 healthcare practices by ensuring that our infrastructure scales reliably under demanding conditions. This role requires strategic foresight to navigate complex technical tradeoffs while maintaining a relentless focus on delivering exceptional user experiences. You will be responsible for translating ambiguous product visions into concrete, robust, and scalable technical solutions.

Key facts

What you'll do

Design and develop end-to-end ML infrastructure and tooling that enables engineering teams to deliver world-class, AI-powered features with speed and reliability.

Build and maintain internal platforms and products that abstract complex AI capabilities, allowing product teams to integrate voice and speech intelligence into their solutions efficiently.

Translate high-level product objectives into detailed engineering plans, ensuring the delivery of scalable and resilient data integration and event processing services.

Partner with product managers and development teams to deeply understand the data lifecycle, advising on optimal ML patterns and architectural tradeoffs for voice and audio workloads.

Elevate engineering standards across the organization by coaching teams on best practices for building, operating, and maintaining sophisticated ML systems.

Write high-quality, performant, and sustainable code that operates effectively within cloud-native environments, ensuring long-term maintainability and reliability.

Monitor the evolution of the AI and voice technology landscape, identifying inflection points and ensuring Weave remains at the forefront of innovation in healthcare communication.

Cut through industry noise to isolate genuine strategic opportunities, leading initiatives that prepare Weave for future challenges and market disruptions.

Shape and enforce company-wide standards for engineering excellence, observability, and reliability, particularly for distributed systems handling sensitive data.

Act as a mentor to senior engineers and staff members, developing the next generation of technical leaders within the Machine Learning Fellowship.

Requirements

Demonstrate extensive experience in building and deploying ML-driven B2B multi-tenant applications that serve external customers at scale in production environments.

Possess deep expertise in distributed systems architecture, with a proven ability to design and operate services that handle hundreds of millions of transactions and terabytes of data reliably.

Bring 15+ years of hands-on experience in Machine Learning or AI, with a specific focus on audio and voice Generative AI solutions deployed at scale.

Showcase deep proficiency with modern ML tools and techniques, including but not limited to LLMs, RAG architectures, Prompt Engineering, and model fine-tuning, specifically for high-scale audio and voice models.

Maintain a strong background in scalable data stores, demonstrating mastery over both relational databases like PostgreSQL at scale and NoSQL solutions such as Bigtable and Redis.

Operate comfortably in cloud-native infrastructure environments, leveraging GCP or AWS, with expertise in Kubernetes, infrastructure-as-code, and highly available system design principles.

Exhibit a track record of successfully leading cross-team technical initiatives that resulted in measurable business outcomes and impacted key performance indicators.

Show the ability to influence stakeholders without direct authority, building consensus across diverse organizational boundaries and articulating technical tradeoffs in clear business terms.

Nice to have

Expertise in deploying customer-facing GenAI solutions in production at scale, with a proven track record of reliability and performance.

Demonstrated experience building low-latency, high-accuracy AI Agents that handle complex conversational flows.

Deep experience delivering Audio or Voice GenAI solutions in production at scale, providing concrete evidence of "been there, done that" rather than theoretical exposure.

A background in compliance-heavy regulated environments such as healthcare or fintech, with a history of navigating regulatory requirements during technical design.

A history of external technical leadership where you have influenced industry standards or shaped engineering practices at other organizations.

Practical notes

This position is remote (US-based).

Reports to: Sr Director of Engineering