* Define and drive the long-term data science and ML strategy, influencing both product direction and organizational priorities
* Lead high-impact research initiatives in ML, GenAI, and Graph ML, push the boundaries of applied science, and establish best practices for scalable adoption
* Partner with engineering and product leadership to align data science innovation with business goals, shaping platform and infrastructure investments
* Mentor and guide staff- and senior-level scientists, set technical direction, and foster a culture of excellence and innovation
* Represent the organization externally through publications, talks, and collaborations, strengthening the company s thought leadership in AI and ML
Requirements:
* Degree in Computer Science, Mathematics, or a related field
* 8+ years of experience in applied ML research and production deployment
* 3+ years of hands-on experience building Generative AI solutions such as RAG, AI Agents, or LLM fine-tuning in production
* Experience with Graph ML and Graph technologies such as GNNs or GraphRAG in production
* Proven track record of end-to-end ownership including design, experimentation, validation, deployment, and scaling of ML systems
* Experience deploying solutions on cloud platforms such as AWS, Azure, or GCP
* Demonstrated ability to solve highly complex, ambiguous, cross-domain problems with measurable business impact
Preferred Qualifications
* MS or PhD in Computer Science, Machine Learning, or a related discipline
* Experience with distributed Big Data and ML platforms such as Spark, Flink, Kafka, PySpark, or Lakehouse
* Recognized track record in the ML and AI community through publications, patents, open-source contributions, or conference talks
* Strong ability to influence at the organizational level by driving strategy and fostering cross-functional alignment
Skills Required
Generative AI, Graph ML, ML Strategy, Distributed Data Platforms, Cloud ML Deployment, End-to-End ML Systems