Note: The job is a remote job and is open to candidates in USA. SpendHQ provides a procurement SaaS platform for spend intelligence and performance management. The AI/ML Engineer will build production infrastructure and MLOps systems for categorization and vendor-normalization models, including training, deployment, monitoring, APIs, and integration with platform workflows.
Responsibilities
- Design, build, and maintain ML pipelines for classification, vendor normalization, and enrichment models
- Develop MLOps practices including CI/CD for model deployment, versioning, and monitoring of accuracy and drift
- Implement feature-store and model registry logic that supports both global (multi-client) and customer-specific models
- Optimize model performance and inference cost across varying dataset sizes
- Build APIs and services that expose classification outputs and confidence scoring to the SpendHQ platform
- Collaborate with Product and Engineering to integrate model outputs into user-facing rule editors and dashboards
- Partner with Data Engineers to manage data ingestion and Core Data Model mapping workflows used as model inputs
- Define success metrics for model speed, scalability, and reliability
Skills
- 5+ years of experience in ML engineering, data engineering, or applied AI roles
- Strong Python experience with ML frameworks (PyTorch, TensorFlow, scikit-learn)
- Experience building and deploying ML pipelines in AWS (S3, SageMaker, ECS, Lambda, IAM)
- Experience building pipelines on cloud or Snowflake/Snowpark environments
- Familiarity with containerization (Docker/Kubernetes), GitHub Actions, and CI/CD practices
- Experience deploying NLP or classification models in production
- Understanding of feature engineering and data quality in multi-tenant SaaS environments
- Collaboration skills to support partnering with data scientists, engineers, and analysts
- Familiarity with LLM integration for text classification and entity resolution
- Interest in applied MLOps and active learning workflows
- Model governance practices including version control, auditability, and access management
- Atlanta is our preferred location, with a hybrid work arrangement at our U.S. headquarters, but we also offer flexible remote options for candidates based on the East Coast
- Experience with procurement, ERP, or spend-data domains (preferred but not required)
Benefits
- Unlimited PTO
- Parental leave
- 401(k)
- Health insurance
- Performance bonus
- Remote work policy
- Flexible working hours
- Equity Program
- Referral bonus
- The development of your knowledge and skills will always be encouraged
- Atlanta is our preferred location, with a hybrid work arrangement at our U.S. headquarters
- Flexible remote options for candidates based on the East Coast
Company Overview
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