Attentive-posted 2 months ago
$215,000 - $290,000/Yr
Full-time • Senior
San Francisco, CA
1,001-5,000 employees

We’re seeking an accomplished Staff Software Engineer to join Attentive’s Machine Learning Platform team as a high-impact individual contributor focused on building the AI and ML infrastructure that powers our AI product suite. You’ll architect and build the foundational platform components that enable AI / ML engineers and data scientists to train, deploy, and serve models and agentic infrastructure with velocity, performance, and reliability at scale. As a Staff-level IC, you’ll operate as a technical force multiplier, setting the technical direction for AI and ML infrastructure across Attentive’s AI organization. You’ll lead through influence and technical excellence, advocating for long-term architectural progress while balancing immediate platform needs. Your work will span strategic initiatives measured in quarters and years, focusing on high-leverage decisions that enable entire teams to ship AI and ML capabilities faster and more reliably.

  • Architect ML platform strategy spanning data pipelines, training infrastructure, and serving layers using cutting-edge tooling like Ray, MLFlow, Metaflow, Argo, and Spark
  • Build and operate production-grade, low-latency ML serving layers with robust model lifecycle systems including champion/challenger testing, automated rollouts, versioning, and rollback capabilities
  • Define and drive Attentive’s agentic stack
  • Provide ML infrastructure perspective in high-level discussions about Attentive’s AI strategy spanning multiple quarters and teams
  • Mentor platform and ML engineers, actively championing team members
  • Build universal interfaces, architectures, and patterns—like data access layers and prediction serving APIs—that bridge platform capabilities with product needs to streamline high-priority ML work across the organization
  • 5+ years focused specifically on ML Platform/MLOps, with deep understanding of gold-standard practices and best-in-class tooling
  • Proven track record of owning and building core components of ML platforms using tools like Spark, Ray, MLFlow, Kubeflow, or Metaflow
  • Experience building and operating a high-throughput agentic stack (MCP / data infrastructure, context store, orchestration, and prompt layer)
  • Strong expertise in Python for both batch processing and online service frameworks
  • Experience designing and operating online and offline inference systems, understanding the critical differences and tradeoffs between them
  • Competitive perks and benefits, from health & wellness to equity
  • US base salary range for this full-time position is $215,000 - $290,000 annually + equity + benefits
  • Equity is a substantial part of the total compensation package
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