Staff MLOps Engineer

Key Responsibilities:

• Build ML infrastructure: Design, operate, and maintain robust systems for low-latency model deployment, distributed inference pipelines, and automated real-time telemetry.
• Scale ranking systems: Move models cleanly from experimentation to production, optimizing trade-offs between latency, throughput, and costs.
• Implement model CI/CD: Build reliable infrastructure for automated model versioning, canary releases, hot-swappable rollouts, and zero-downtime rollbacks.

What We Value:

• Rigorous systems & scientific thinking: Balance algorithmic complexity with microsecond latency constraints.
• Uncompromising ownership: Treat production stability and platform efficiency as a personal reflection of code quality.
• Pragmatic speed: Rapidly design and deploy robust infra prototypes without accumulating debilitating tech debt.

What We Offer:

• High-impact influence: A foundational, high-autonomy role shaping core deployment and serving topology.
• Pioneering systems: Opportunity to build and scale category-defining, low-latency ML platforms.
• Top-tier reward: Highly competitive base salary, uncapped performance metrics, and meaningful early-employee equity.