Senior Applied Scientist, Personalization & Agentic Systems

Responsibilities

• Design, build, and operate production-grade agentic personalization systems that adapt to user behavior and context
• Research, develop and implement ML models using Transformers, LLMs, and classical ML algorithms for search and recommendation use cases
• Be proficient in agentic frameworks (e.g., LangGraph ) and building systems that orchestrate multi-step reasoning, tool use, and decision-making workflows.
• Be proficient in optimized inference engines/frameworks like vLLM , TensorRT
• Productionize ML- and LLM-powered workflows, including inference services, orchestration, monitoring, and iteratio n
• Build agentic systems that leverage agent memory, retrieval-augmented generation (RAG), and tool ecosystems/APIs to deliver context-aware personalization and recommendations
• Build and evolve data and feature pipelines that power personalization, experimentation, and feedback loops
• Develop robust methods to evaluate LLM performance, ensuring ethical AI practices
• Monitor and improve deployed models based on real-world performance metrics and customer feedback
• Collaborate with cross-functional teams including engineering, product management, and operations to translate research into production systems

Minimum Qualifications

• BS or MS in Computer Science, Engineering, or a related field
• 6 or more years of professional software engineering experience, including ownership of production systems
• Strong experience building AI systems in cloud environments, AWS preferred
• Hands-on experience delivering AI, ML, or LLM-powered systems into production
• Experience with AI agents, orchestration frameworks, or hybrid reasoning systems
• Experience with MLOps practices, experimentation frameworks, and model monitoring
• Proficiency in one or more programming languages such as Python, Java, or equivalent
• Experience working with data systems including RDBMS, NoSQL, data warehouses, and streaming platforms
• Strong understanding of system design, scalability, and operational excellence
• Ability to work autonomously while collaborating effectively across engineering, product, and data teams
• Excellent communication skills and ability to influence technical decisions
• Experience building personalization, recommendation, or insight platforms
• Experience with real-time or event-driven architectures
• Exposure to AI governance, privacy, or safety considerations at scale
• Experience mentoring Junior engineers or acting as a technical lead on complex initiatives
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