Lead Enterprise AI Scientist & Data Architect

Socket.dev

Bellevue (WA)

Hybrid

USD 283,000 - 606,000

Full time

4 days ago
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Job summary

SAP is seeking a senior AI/ML leader to join the Data and Applied Science team in the Seattle area. You will evolve the semantic and contextual foundation of SAP's AI, leveraging SAP Datasphere, HANA Cloud, and Databricks to deliver scalable AI capabilities across enterprise data.

You will partner with product, engineering, and business teams to drive measurable outcomes. Applicants bring a strong background in ML, deep learning, and generative AI, with hands-on experience deploying models in

Qualifications

  • Master's degree or PhD in Computer Science, Applied Mathematics, Statistics, Engineering, or related quantitative fields.
  • 10+ years of experience in machine learning, deep learning, generative AI, and LLMs with real-world datasets.
  • Strong Python and SQL with production-grade development and ML libraries.
  • Experience deploying AI/ML solutions in production environments.
  • Familiarity with Databricks and cloud platforms (AWS, Azure, GCP).

Responsibilities

  • Design, develop, evaluate, and operationalize end-to-end ML and AI solutions.
  • Translate business challenges into concrete AI use cases and technical designs.
  • Collaborate with product, engineering, and customer-facing teams to scale solutions.
  • Work with enterprise data models, semantic data solutions, and knowledge graphs.

Skills

Python
SQL
PyTorch
TensorFlow
scikit-learn
Communication

Education

Master's degree or PhD in Computer Science, Applied Mathematics, Statistics, Engineering, or related quantitative fields

Tools

Databricks
SAP Datasphere
SAP HANA Cloud
AWS
Azure
GCP

Job description

SAP is seeking a senior AI/ML leader to join the Data and Applied Science team in the Seattle area. You will evolve the semantic and contextual foundation of SAP's AI, leveraging SAP Datasphere, HANA Cloud, and Databricks to deliver scalable AI capabilities across enterprise data.

You will partner with product, engineering, and business teams to drive measurable outcomes. Applicants bring a strong background in ML, deep learning, and generative AI, with hands-on experience deploying models in

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