# Staff Machine Learning Engineer, Gen AI | Voice & Speech

**Company:** [Weave](https://hotfix.jobs/companies/weave)
**Location:** Remote
**Role:** ML Engineering
**Experience:** 15+ years
**Skills:** Machine Learning, Generative AI, MLOps, LLMs, Retrieval-Augmented Generation, Prompt Engineering, Fine-Tuning, Kubernetes, Postgres, Redis, Bigtable, Spanner, AWS, GCP, Distributed Systems
**Posted:** 2026-08-10

> Leads the architecture and delivery of scalable machine learning infrastructure and customer-facing voice and audio generative AI solutions. The role requires extensive production ML experience, distributed systems expertise, cloud-native operations, and technical leadership across engineering teams.

## Job Description

## What You Will Own

### Infrastructure & Delivery
- Design and develop ML infrastructure, tooling, and models to help teams deliver world-class experiences.
- Build internal and external products and platforms that enable teams to incorporate AI into features and customer-facing products.
- Translate product goals into actionable engineering plans and build scalable, resilient services for data integration and event processing.

### Cross-Team Problem Solving
- Help product and development teams understand the data lifecycle.
- Consult with teams on common ML patterns and tradeoffs.
- Coach and collaborate across teams to elevate technical standards.
- Write high-quality, performant, sustainable, and testable code in a cloud environment.

### Strategic Technical Leadership
- Monitor the industry landscape and anticipate technological advances.
- Identify strategic value and lead initiatives that prepare the organization for emerging challenges.
- Shape company-wide standards for engineering excellence, observability, and reliability in distributed systems.

### Mentorship & Organizational Capability
- Mentor Staff and Senior Engineers across the fellowship.
- Elevate architectural thinking through design reviews, documentation standards, and hands-on guidance.
- Build organizational capability that persists beyond individual contributions.

## Requirements
- Experience building and deploying ML-driven B2B, multi-tenant applications in production at scale for external products and customers.
- Deep expertise in distributed systems architecture, including services handling 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 generative AI solutions at scale.
- Deep expertise with modern ML tools and techniques, including LLMs, retrieval-augmented generation, prompt engineering, fine-tuning, high-scale audio and voice models, and LLM evaluations.
- Strong background with scalable relational and NoSQL data stores, including PostgreSQL at scale, Vitess, Spanner, Bigtable, and Redis.
- 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 with measurable business outcomes.
- Ability to influence without direct authority, build consensus across organizational boundaries, and translate technical tradeoffs into business terms.

## Nice-to-Haves
- Expertise with customer-facing generative AI in production at scale.
- Experience building low-latency, high-accuracy AI agents.
- Mandatory deep experience delivering voice or audio generative AI solutions to external products at scale.
- Experience in compliance-heavy environments such as healthcare or fintech.
- External technical leadership through open-source contributions, conference speaking, or published technical writing.
- Conviction in technical discussions combined with openness to better ideas.

## Benefits & Compensation
- Remote position for US-based candidates.
- Employment is contingent upon successful completion of a background check.

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