Senior AI/ML Engineer

. Bring machine learning into supply chain and logistics systems for a federal health customer.

Posted 9/25/2026full-timeRemote • United StatesSenior💰 $195,000 - $208,000 per yearWebsite

Tools & technologies

AWSAzureCloudKerasPyTorchTensorflow

Key responsibilities & impact

Bring machine learning into supply chain and logistics systems for a federal health customer.
Take mission problems from framing through a deployed model.
Decide what is worth modeling and what is not.
Own the analytical approach end to end.
Translate operational problems into an end-to-end analytical approach.
Develop, train and evaluate models across forecasting, classification and natural language tasks.
Own the path from notebook to production, including retraining, monitoring and drift detection.
Work with data engineering on data collection, cleansing and integration.
Communicate results and their limits to decision-making stakeholders.

What you’ll need

Master's degree and 18+ years of analytics, data science or machine learning experience.
Production experience with TensorFlow, PyTorch or Keras, including GPU-accelerated training.
Demonstrated ownership of a model from problem framing through deployment and monitoring.
Building the data pipelines your models depend on, including storage and retrieval at scale.
Deploying models inside a government-controlled environment rather than a public AI service, including delivery of models and weights and meeting federal requirements for bias evaluation and documentation.
Experience validating model results and communicating uncertainty to non-technical stakeholders.
Ability to obtain and maintain a federal background investigation (Public Trust).
Applicants need to be a US Citizen to be considered for the position.
Applicants must have physically resided in the United States for a minimum of 3 years due to background investigation requirements.
Preferred: Experience on federal health IT programs.
Preferred: Time series forecasting applied to inventory, demand or logistics.
Preferred: MLOps tooling experience (MLflow, Kubeflow, SageMaker or equivalent).
Preferred: Natural language processing on operational or clinical text.
Preferred: Cloud experience in government regions (AWS GovCloud, Azure Government).
Preferred: Experience in SAFe at scale, including Program Increment planning.
Preferred: Familiarity with federal IT governance and approved-tooling processes.

Comp & perks