AI/ML Engineer

About the Role Design, build, and deploy ML and Generative AI solutions from development through production. Drive the productionization of AI/ML models by building scalable pipelines, RAG solutions, and cloud-native AI applications. Roles & Responsibilities • Design, build, and deploy ML and Generative AI pipelines from development through production. • Implement Retrieval-Augmented Generation (RAG) solutions to enhance AI-driven applications with contextual data. • Develop and integrate APIs and orchestration workflows to support scalable AI systems. • Drive end-to-end productionization of AI/ML models, ensuring reliability, scalability, and performance. • Partner with engineering, data, and product teams to operationalize AI use cases in production environments. • Optimize model performance, monitoring, and lifecycle management within cloud-native environments. Key Skills • AI/ML Engineering & Production Deployment • Generative AI & RAG Architectures • MLOps (Model Deployment, Monitoring & CI/CD) • AWS (SageMaker, Lambda, S3, ECS/EKS) • Python, PyTorch, TensorFlow, LangChain, Docker & Kubernetes Benefits (W2) • Health insurance • Health savings account • Dental insurance • Vision insurance • Flexible spending accounts • Life insurance • Retirement plan EEO Statement All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or status as a protected veteran.