Platform Engineer

• Architect the data foundation for large scale scientific and engineering output, keeping results clean, queryable, reusable, and ready for model training.
• Model domain specific scientific data so the same datasets can support interactive analysis, automation, and downstream machine learning workflows.
• Build scalable data processing patterns across object storage, analytical stores, and training optimized formats.
• Create machine learning data pipelines for curation, deduplication, formatting, evaluation sets, and regression tracking.
• Build and operate training and fine tuning pipelines for models used in scientific and workflow driven products.
• Develop intelligent workflow interfaces that connect user intent, structured platform capabilities and executable workflows without exposing unnecessary complexity to users.
• Own model evaluation, benchmarking, automated scoring, and quality tracking so each iteration is measurable.
• Set data and AI engineering standards for the team and turn them into code, documentation, and reusable patterns.

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Principal Software Engineer, AI & Data Platform