about 3 hours ago
Responsibilities
- Design and develop ML infrastructure, tooling, and models that enable teams to deliver AI-powered customer experiences.
- Build internal and external products and platforms that integrate AI into engineering features and customer-facing products.
- Translate product goals into actionable engineering plans and build scalable, resilient services for data integration and event processing.
- Consult with product and development teams on data lifecycles, ML patterns, and technical tradeoffs.
- Write high-quality, performant, sustainable, and testable code in a cloud environment.
- Lead strategic technical initiatives, monitor technological developments, and identify opportunities with genuine strategic value.
- Shape company-wide standards for engineering excellence, observability, reliability, and distributed systems.
- Mentor Staff and Senior Engineers and elevate architectural thinking through design reviews, documentation, and hands-on guidance.
- Partner with Engineering Managers, Staff Engineers, and cross-functional stakeholders to drive architectural coherence across data and AI/ML teams.
Requirements
- Demonstrable experience building and deploying production ML-driven B2B multi-tenant applications at scale for external 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, focused on or including large-scale audio and voice GenAI solutions.
- Expertise with 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.
- Preferred expertise with customer-facing GenAI in production at scale and low-latency, high-accuracy AI agents.
- Mandatory deep production experience delivering meaningful voice or audio GenAI solutions to external products at scale.
- Preferred experience in compliance-heavy environments such as healthcare or fintech.
- Preferred external technical leadership through open-source contributions, conference speaking, or published technical writing.
Benefits
- Remote position; US-based.
- Employment is contingent upon successful completion of a background check.
- Equal opportunity employer with disability and accommodation support.