Company Overview:

Procurement Sciences is at the forefront of transforming the multi-billion-dollar government contracting industry with Awarded AI, our cutting-edge platform designed to help businesses excel in government sales. We simplify complex processes, drive revenue growth, and deliver real cost savings through unmatched efficiency. As a leading venture-backed SaaS company founded by seasoned GovCon experts, we are not just participants in the AI revolution; we are shaping it by solving the industry’s toughest challenges. Our “One Team, One Fight” culture values creativity, accountability, and forward-thinking, and we invite driven builders and innovators to help us develop high-performing teams. Ranked among the top 10 percent of fastest-growing SaaS companies and on a clear path to becoming a unicorn, we are seeking top talent to join our early team and play a key role in building the next great AI software company.

Job Description: 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.

Key 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

Ideal Candidate:

• 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

Required Experience:

• 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

Desired Experience:

• Experience with LangChain, LangGraph, or similar LLM orchestration frameworks
• Knowledge of data orchestration platforms like Dagster or Airflow
• Background in search systems, embeddings, or information retrieval

Requirements:

• 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.

Compensation and Benefits:

• Competitive salary with stock options in a rapidly growing, venture-backed company.
• Comprehensive health plan, ensuring you and your loved ones are well taken care of.
• Flexible work arrangements, including full remote work capabilities, to balance your professional and personal life.
• Extensive professional development opportunities, providing a fast track for career advancement.

Notice:

Background Check Required. As part of our employment process, a background check is required. This may include a review of your credit history, criminal records, and employment verification, conducted in compliance with the Fair Credit Reporting Act (FCRA). By applying, you acknowledge and consent to this process.

Compensation Range: $150K - $200K