Overview
What You’ll Be Doing
We are seeking an experienced AI/ML Engineer to join our team. As an AI/ML Engineer at Cadmus, you will support advanced AI projects that leverage both traditional machine learning and modern generative AI technologies using cloud-native services. Your primary responsibilities will involve architecting, designing, developing, deploying, and maintaining machine learning and AI models in production environments, with emphasis on integrating GenAI capabilities into scalable solutions. Position requires US Citizenship or Permanent Resident. Position can be US based Remote.
Who We Are
Cadmus is a technology-empowered strategic consulting firm with more than 1,300 experts dedicated to serving government, commercial, and non-governmental organizations worldwide. We help our clients achieve their goals and drive lasting, impactful changes by leveraging transformative digital solutions and unparalleled expertise across domains.
At Cadmus, we look for team players and problem solvers who are driven to use their unique perspectives and intellectual curiosity to help deliver breakthrough solutions that achieve transformative goals. As a member of our team, you’ll collaborate with leading experts to support our clients across the globe. We offer competitive compensation, outstanding health care and retirement benefits, a vibrant and collaborative work environment, and ample opportunities for professional growth.
Join Cadmus. Together, we are strengthening society and the natural world. For more information, visit www.cadmusgroup.com.
Responsibilities
+ Work with cross-functional team members to understand business needs and develop AI/ML solutions incorporating generative AI technologies.
+ Design scalable AI/ML systems, implement, and deploy GenAI applications including large language models, multimodal AI systems, and retrieval-augmented generation (RAG) architectures for enterprise knowledge management and chatbot applications.
+ Develop multi-agent AI systems using frameworks such as Langgraph with coordinated complex agent interactions.
+ Participate in code reviews and establish coding best practices for developing and maintaining clean, efficient, and well-documented Python code.
+ Drive end-to-end model development lifecycle from research to production deployment for both traditional ML and GenAI workflows.
+ Lead fine-tuning initiatives for large language models and establish evaluation frameworks for