Job description

Job Responsibilities - 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

Requirements