AI/ML Engineer

Role overview

An opportunity to operate as an applied machine learning engineer focused on productionizing ML systems end to end. The role centers on building reliable MLOps frameworks and pipelines, deploying models at scale, and partnering across engineering and data teams to integrate ML into mission-critical applications.

Responsibilities

- Develop MLOps frameworks and workflows tailored to a variety of domains and applications. - Build, train, deploy, and maintain machine learning models in production environments. - Design and operate end-to-end ML pipelines covering data ingestion, feature engineering, training, validation, deployment, and monitoring. - Implement MLOps tooling such as CI/CD pipelines, model versioning, model registries, feature stores, and automated retraining workflows. - Deploy and optimize ML solutions using cloud platforms and containerized technologies including Docker, Kubernetes, SageMaker, Vertex AI, or Azure ML. - Collaborate across engineering and data teams to integrate scalable ML into applications while monitoring performance and addressing model drift.

Requirements

- Hands-on experience building, training, deploying, and maintaining machine learning models in production. - Strong proficiency in Python and experience with one or more frameworks such as PyTorch, TensorFlow, Scikit-learn, XGBoost, or Hugging Face. - Experience developing end-to-end ML pipelines and MLOps practices, including CI/CD, model versioning, registries, feature stores, monitoring, and automated retraining. - Experience deploying ML models using cloud-native or containerized technologies such as Docker, Kubernetes, SageMaker, Vertex AI, or Azure ML. - Experience monitoring production ML systems, troubleshooting model performance, and addressing model drift. - U.S. citizenship required; dual citizenship is not permitted.

Nice to have

- Advanced degree in a STEM field, with a Ph.D. preferred but not required.

Benefits and work setup

- Compensation varies by location and is set within published pay ranges for specified U.S. states and the District of Columbia. - Reasonable accommodations are available for candidates and employees with disabilities or religious observances. - Applications are reviewed on a rolling basis with no fixed deadline.