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Staff AI Engineer - GenAI
Staff AI Engineer - GenAI
The Staff AI Engineer - GenAI will join a high-performing Data Science & MLE team to drive competitive value through scalable AI solutions, focusing on personalization and user engagement using Generative AI and advanced machine learning. Key responsibilities include leading end-to-end AI transformations, developing and deploying ML algorithms and RAG systems, and providing strategic product guidance through data-driven recommendations.
About the role
Role: Staff AI Engineer - GenAI
Join a high-performing Data Science & MLE team whose mission is to drive competitive value through scalable AI solutions. The team builds models that enhance user experiences, enable better decision-making, improve operational efficiency, and shape the regional AI ecosystem. As a senior technical leader, you’ll help define the future of personalization and user engagement using Generative AI and advanced machine learning.
Key Responsibilities
- Lead end-to-end AI transformation focused on personalization in a consumer-facing application.
- Define and execute a long-term vision for customer acquisition and engagement strategies powered by data and AI.
- Conduct exploratory analysis to understand user behavior, discover optimization opportunities, and develop behavior models to inform product enhancements.
- Design and deploy data/ML instrumentation to extract insights and optimize the product experience.
- Provide strategic product guidance through data-driven recommendations, experimentation insights, and root cause analyses.
- Build and scale machine learning algorithms and pipelines to production using big data technologies.
- Develop and deploy retrieval-augmented generation (RAG) systems and LLM-based applications.
- Design and evaluate A/B tests and communicate results across cross-functional teams.
- Define, implement, and monitor key performance metrics for AI-driven product features.
- Stay up to date with industry advancements in data processing and AI/ML, and introduce best practices into the organization.
Requirements
- 7+ years of experience in data science, machine learning, and AI development across structured and unstructured data.
- Advanced degree (Master’s or PhD) in Computer Science, Engineering, Mathematics, Statistics, or a related field (preferred).
- Deep experience in personalization, search, or recommendation systems (3–4 years in a product-focused environment).
- Expertise in deep learning architectures (e.g., attention models, transformers, retrieval models).
- Hands-on experience with LLMs and GenAI technologies.
- Strong programming and problem-solving skills with proficiency in Python, SQL, Spark, and Hive.
- Deep understanding of classical and modern ML techniques, A/B testing methodologies, and experiment design.
- Solid background in ranking, recommendation, and retrieval systems.
- Familiarity with large-scale data tools (Hadoop, BigQuery, Amazon EMR, etc.).
- Experience with BI tools and visualization platforms such as Tableau, Qlik, or MicroStrategy.
- Bonus: Experience with geospatial data and advanced analytics platforms.