Collaborate with ML engineers, data scientists, and product teams.
Build scalable ML infra services across notebooks, training, experimentation, and serving.
Create tools enabling ML engineers to move from experimentation to production.
Own end-to-end ML workflows across data, analytics, and AI/ML platforms.

🎯 Requirements

2+ years in software development with distributed systems.
Full lifecycle software development experience.
Production ML platforms, MLOps, or LLM apps experience.
Experience running high-availability, low-latency systems.
Experience partnering with other teams to drive outcomes.
Pragmatic approach: know when to aim for ideal vs. practical solutions.

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