Chief AI Scientist — Enterprise Data & Semantics

Socket.dev

Palo Alto (CA)

On-site

USD 180,000 - 240,000

Full time

5 days ago
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Job summary

SAP's Data and Applied Science team seeks a senior AI/ML leader to build semantic, enterprise-focused AI solutions. You will transform complex business data into actionable knowledge across master data, process semantics, and domain relationships.

Responsibilities include designing ontologies, deploying ML workflows on Databricks and cloud platforms, and partnering with product and engineering to deliver scalable, production-ready AI for SAP customers.

Qualifications

  • Master's degree or PhD in Computer Science, applied math, statistics, engineering or related field.
  • 10+ years in ML, deep learning, statistical modeling, generative AI and LLMs with real datasets.
  • 10+ years in ML/data science, AI research, or semantic data systems in industry or academia.
  • Strong Python and SQL, with production-grade development and ML libraries.
  • Experience deploying and operating AI/ML solutions in production environments.
  • Experience with Databricks and cloud environments (AWS/Azure/GCP).
  • Excellent communication and collaboration in agile settings.

Responsibilities

  • Design, develop, evaluate, and operationalize end-to-end ML/AI solutions.
  • Turn ambiguous business challenges into concrete AI use cases and designs.
  • Develop AI capabilities including generative AI and LLM-based solutions.
  • Collaborate with product, engineering, and customer-facing teams to ensure scalable solutions.

Skills

Python
SQL
PyTorch
TensorFlow
scikit-learn
LLMs
Production ML
Data preprocessing
Feature engineering
Experimentation
Analytical modeling
Big data
Agile
Communication

Education

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

Tools

Databricks
AWS
Azure
Google Cloud Platform

Job description

SAP's Data and Applied Science team seeks a senior AI/ML leader to build semantic, enterprise-focused AI solutions. You will transform complex business data into actionable knowledge across master data, process semantics, and domain relationships.

Responsibilities include designing ontologies, deploying ML workflows on Databricks and cloud platforms, and partnering with product and engineering to deliver scalable, production-ready AI for SAP customers.

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