Machine Learning Engineer
AI Squared10 months ago
Washington, DC, USASenior
Responsibilities
- Design, implement, and maintain ML deployment pipelines for scalable production systems.
- Operationalize LLMs and other AI/ML models for high availability and reliability.
- Build monitoring, logging, and alerting systems to track model performance and detect drift.
- Transition models from research and prototypes into production-ready deployments with data scientists.
- Develop automated ML workflow deployment pipelines integrating testing and validation.
- Optimize ML model runtime performance across AWS, GCP, Azure, and distributed systems.
- Use Docker and Kubernetes to enable reproducible and scalable ML systems.
- Collaborate with data scientists, data engineers, product teams, and other stakeholders on platform-aligned ML systems.
Requirements
- 5+ years of experience as a Machine Learning Engineer, MLOps Engineer, or in a similar role.
- Proven experience deploying and maintaining machine learning models in production at scale.
- Hands-on experience with ML lifecycle tooling such as MLflow, Kubeflow, SageMaker, or Vertex AI.
- Strong proficiency in Python and familiarity with PyTorch or TensorFlow.
- Deep knowledge of Docker and Kubernetes for production ML systems.
- Expertise with AWS, GCP, or Azure for ML deployment and scaling.
- Strong understanding of MLOps best practices, monitoring, and automation.
- Strong problem-solving, communication, and collaboration skills.
Benefits
- Hybrid work arrangement in Washington, DC.
Tech Stack
Categories
About AI Squared
AI Squared builds a low‑code platform (UNIFI and Sparx) to embed AI and analytics into existing business applications, capture user feedback, and orchestrate secure deployments. It sells to enterprises and federal agencies seeking to operationalize LLMs and other ML models with governance and monitoring. Founded in 2021 and headquartered in Mountain View, it is privately held and Series A–funded; customers include financial institutions, supply chain organizations, and the U.S. Department of Defense.