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docker python kubernetes pytorch pyspark📋 Description
- Lead ML projects across multiple teams; guide tech direction and platform capabilities.
- Collaborate with scientists, engineers, product, and success teams to deliver production ML systems.
- Embrace AI-first practices and Claude Code to accelerate development.
- Work in small, collaborative teams on end-to-end ML infra.
- Keep processes lightweight with rigorous ML experimentation.
🎯 Requirements
- 8+ years of experience building production ML systems.
- Technical leadership across multiple ML projects.
- Expertise in ML deployment, model serving, feature engineering, and monitoring.
- Python software engineering; ML frameworks like XGBoost, PyTorch, PySpark.
- Cloud-native ML infra, containerization, and orchestration (Kubernetes, Docker).
- AI-first development with coding assistants such as Claude Code.
- Turn ambiguous ML infra problems into actionable plans.
- Align ML strategy with priorities and customer needs.
🎁 Benefits
- Hybrid work: 3 days in the Seattle office with remote flexibility.
- 100% employee healthcare coverage and transportation subsidies.
- Self-managed PTO and flexible work arrangements.
- Equity and stock options as part of total compensation.
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