Applied Scientist Ii

Job description

Design, develop, and deploy AI/ML systems end-to-end, covering data ingestion, feature engineering, model training, evaluation, and production integration. Build and optimize Generative AI and LLM-based systems, including agentic workflows, prompt engineering, RAG, and fine-tuning. Write production-grade code in Python, C#, etc., with emphasis on scalability, performance, security, testability, and maintainability. Partner with engineering, product management, and applied science teams to translate customer/business requirements into robust technical solutions. Ship and operate large-scale AI services in the cloud, owning reliability, latency, throughput, accuracy, and cost efficiency. Define and execute model evaluation strategies, including offline experimentation, online monitoring, drift detection, bias analysis, and feedback loops. Implement MLOps practices, including model CI/CD, versioning, rollout strategies, observability, and live-site monitoring. - Apply Responsible AI principles covering privacy, security, explainability, fairness, and compliance throughout development and deployment. Stay current with advances in GenAI, LLM frameworks, and ML infrastructure, and evaluate their applicability to enterprise security scenarios. Bachelor's degree in Computer Science, Data Science, Engineering, or a related technical field. 5+ years overall experience, including hands-on model development experience and writing production-quality code Solid understanding of ML fundamentals, model evaluation, experimentation, and performance trade-offs. Experience building or operationalizing LLM / Generative AI systems, including RAG, prompt engineering, or agent-based architectures. Ability to collaborate across disciplines and operate autonomously at senior IC scope.