Senior AI and ML Engineer, Procurement Sciences AI

• If you're ready to join a team that's reshaping the industry landscape, leading in AI, and on the path to becoming the next unicorn, Procurement Sciences is your new home. Join us on our mission to democratize government contracting success and shape the future of this vital sector
• Strong foundation in traditional machine learning with production deployment experience
• Excited to apply ML fundamentals to modern AI workflows including RAG and basic agent systems
• Collaborative problem solver who thrives in startup environments with evolving requirements
• Eager to learn new technologies while leveraging proven ML engineering practices
• 5+ years deploying ML models in production (classification, recommendations, or similar)
• Strong Python proficiency with ML libraries (scikit-learn, pandas, numpy) and deployment frameworks
• Experience with ML infrastructure: model serving, monitoring, and data pipelines
• Familiarity with foundation model APIs (OpenAI, Anthropic, etc.) and vector databases
• Track record of building systems that handle real user traffic and data
• U.S. citizenship with the ability to pass a Federal Background Check and Identity Verification
• While formal education is not a strict requirement, a Bachelor's or Master’s degree in Computer Science, Engineering, or a related field is preferred

Desirable

• AI is central to our operations, driving the development of cutting-edge features and empowering our customers with intelligent AI agents
• Our "One Team, One Fight" culture fuels our disruptive spirit, redefining possibilities with AI as a force multiplier. At Procurement Sciences, innovation is more than a buzzword—it's in our DNA, where AI serves as a playground for challenging norms and shaping the future of GovCon
• We are seeking a Machine Learning Engineer to build and scale classification and recommendation systems that power our core product
• You'll work closely with ML leadership to apply proven ML fundamentals across diverse technical challenges, including integrating LLM-based features into our existing workflows
• In this role, you will own traditional ML systems while gaining hands-on experience with modern AI components like RAG pipelines and agent frameworks
• Your work will directly impact product performance through better recommendations, search quality, and user classification
• You'll collaborate with a talented team to solve real technical problems in a fast-growing SaaS environment
• Build, deploy, and maintain production classification and recommendation systems serving thousands of users
• Design and implement ML pipelines for training, evaluation, and monitoring of traditional ML models
• Integrate LLM APIs and vector databases into existing ML workflows to enhance product capabilities
• Collaborate with product and engineering teams to translate business requirements into scalable ML solutions
• Optimize model performance, system reliability, and inference latency across our ML stack