Data Scientist

• Build and Launch Enterprise-Scale Generative AI Products Design, develop, and deploy end-to-end Generative AI systems —including chat agents, headless agents, and decision-automation orchestrators—that drive measurable business impact.
• Deliver real-time inferencing pipelines using GenAI, NLP, speech, vision, forecasting, classification, and optimization models to power agent behavior.
• Own models “from prototype to production,” ensuring reliability, low latency, and high-volume performance.
• Continuously test evolving AI frameworks (e.g., LangChain, LlamaIndex, CrewAI, custom orchestration loops) and build POCs that influence enterprise adoption.
• Assess model architectures, prompt-optimization strategies, memory handling, and action-selection loops.
• Identify and mitigate real-world failure modes such as hallucination, improper tool invocation, context drift, or scaling constraints.
• Build distributed, production-grade AI systems using GCP, AWS, or Azure, and deploy agents using Kubernetes, Kafka, Airflow, vector databases, and scalable microservices.
• Solve operational challenges including container cold starts, vector-store scaling, memory fragmentation, GPU-CPU balancing, index rebuilds, and multi-shard latency.
• Work independently with product, engineering, and business partners to translate ambiguous business problems into precise analytical and technical requirements.
• Evaluate processes, identify automation opportunities, and deliver AI solutions that improve revenue, reduce cost, or eliminate manual tasks.
• Teach cross-functional partners how AI systems work, how to evaluate them, and how to integrate them into their operations.

Data Scientist III

Senior Data Scientist

Staff Data Scientist

Distinguished Data Scientist

Director, Data Science