Senior System Engineer IRC

Description

• Primary platform:
  Google Cloud Platform (inference, deployment automation, experimentation, sampling)
• Production integration:
  Java-based streaming pipelines (model integration layer)
• Infrastructure:
  Hybrid – on‑premise streaming + GCP serving stacks
• Distributed systems:
  Working knowledge required for debugging and end‑to‑end testing (not deep expertise)
• Strong foundation in ML inference, deployment, and quality testing
• Demonstrated ability to ramp up quickly on new and unfamiliar tech stacks – this is the single most important trait
• End‑to‑end problem‑solving mindset – can own a problem from model handoff to user‑facing behavior
• Core ML knowledge sufficient to benchmark models and collaborate with researchers
• Experience deploying models in cloud environments, ideally GCP

• Perform model sampling to support quality evaluation and researcher feedback loops
• Debug issues across the full stack – from inference layer down to streaming pipelines
• Partner with ML researchers to provide benchmarking feedback and guide inference decisions – requires enough core ML knowledge to have a meaningful technical handshake
• Adapt rapidly to non‑standard and evolving tech stacks across hybrid (on‑prem + GCP) infrastructure

• Evaluate and benchmark new ML inference frameworks to guide production decisions
• Deploy models to GCP and integrate them into production applications and Java‑based streaming pipelines
• Own deployment automation end‑to‑end – from model handoff through live serving
• Monitor how models behave in production for real end‑users
• Design and execute benchmarking, performance testing, and quality testing on ML models
• Bachelor’s or Master’s degree in Computer Science, Computer or Electrical Engineering, Mathematics, or a related field