Procurement Sciences is seeking to transform the government contracting industry with its AI platform, Awarded AI, by simplifying processes, boosting revenue, and delivering cost savings. The company aims to solve enduring industry challenges by leveraging AI to enhance competitiveness and operational excellence.
Requirements
- 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
- 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
Responsibilities
- 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
Other
- Collaborative problem solver who thrives in startup environments with evolving requirements
- Eager to learn new technologies while leveraging proven ML engineering practices
- U.S. citizenship with the ability to pass a Federal Background Check and Identity Verification.
- Background Check Required.
- 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.
