Overview
Lead Platform Systems engineering for AIMS, setting technical strategy, scaling the team, and guiding distributed systems and AI infrastructure modernization.
What you'll do
- Define the long-term technical strategy and execution roadmap for Platform Systems.
- Set engineering standards for observability, reliability, on-call practices, and development workflows.
- Own observability, evaluation, and tooling subsystems for next-generation ML architecture.
- Hire, develop, and retain engineers across seniority levels.
- Partner with AIMS and infrastructure leaders on strategic planning and investments.
- Guide AI stack modernization and migration alignment across partner teams.
- Navigate ambiguity across platform engineering, ML infrastructure, and organizational change.
What you'll need
- Significant experience leading platform or infrastructure engineering organizations operating distributed systems at scale.
- Strong technical depth in distributed systems architecture and design tradeoffs.
- Hands-on experience building subsystems for advanced agentic architectures or complex model systems.
- Experience with ML infrastructure supporting online and offline training pipelines.
- Track record of building high-performing teams and developing senior technical talent.
- Track record of improving reliability, reducing infrastructure costs, and increasing engineering velocity.
- Ability to influence across a large organization without direct authority.
Nice to have
- Experience operating large-scale infrastructure and distributed systems.
- Experience building ML platforms for recommendation, ranking, or personalization systems.
- Working knowledge of generative AI and traditional machine learning approaches.
- Understanding of the end-to-end ML lifecycle.
Details
- Remote in the USA.
- Full-time salaried role.
- Annual salary range: $523,000–$920,000.
Read the full description and apply on the company’s own careers page.
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