AI Platform & Cloud Engineer

Confirmed live in the last 24 hours

Axle Informatics

Rockville, MD

Hybrid

Posted February 18, 2026

Job Description

(ID: 2025-0914)

Axle is a bioscience and information technology company that offers advancements in translational research, biomedical informatics, and data science applications to research centers and healthcare organizations nationally and abroad. With experts in biomedical science, software engineering, and program management, we focus on developing and applying research tools and techniques to empower decision-making and accelerate research discoveries. We work with some of the top research organizations and facilities in the country including multiple institutes at the National Institutes of Health (NIH).

Benefits We Offer:

100% Medical, Dental & Vision Coverage for Employees
Paid Time Off and Paid Holidays
401K match up to 5%
Educational Benefits for Career Growth
Employee Referral Bonus
Flexible Spending Accounts:
- Healthcare (FSA)
- Parking Reimbursement Account (PRK)
- Dependent Care Assistant Program (DCAP)
- Transportation Reimbursement Account (TRN)

Overview

The AI Platform & Cloud Engineer will help sustain the hybrid cloud production environment for the SOM Center’s data ecosystem. This role serves as the technical interface between Data Science and IT, focusing on Platform Engineering: building the internal developer platform (IDP) that utilizes the IT-managed Kubernetes infrastructure and cloud resource to scale resources for workflow orchestration, knowledge graph data pipelines, and distributed model inference.

Responsibilities:

IT Collaboration & K8s Support: Collaborate closely with the dedicated IT team to define compute requirements and orchestrate workloads on the new Kubernetes cluster. The engineer will not manage the cluster directly but will ensure data science applications are correctly containerized and configured to run efficiently on the infrastructure provided by IT.
Infrastructure Strategy: Define the Infrastructure as Code (IaC) specifications for application-level resources, working with IT to ensure on-premises GPU clusters and public cloud environments (GCP/AWS) are utilized effectively.
Refactoring & Model Serving: Transform experimental code (Jupyter Notebooks, R scripts) developed by NLP and Omics researchers into robust, containerized software packages. Deploy and optimize model inference servers (e.g., vLLM, Triton Inference Server) to expose AI models as reliable internal APIs.
Workflow Orchestration: Deploy and maintain the Workflow Orchestration platform (e.g., Apache Airflow, Prefect, or Dagster) to manage dependenc