Senior ML Engineer: Defense AI for Mission-Centric Systems

Carnegie Mellon University; Arlington (VA); On-site; USD 130,000 - 190,000; Full time

Benefits offered by this job

Tuition benefits

Paid time off

Life and disability insurance

Bus pass

Job summary

Carnegie Mellon University's SEI AI Division seeks a Machine Learning Engineer to transform research ideas into mission-ready prototypes for defense and national security applications. You will design ML models, build data pipelines, and deploy secure, scalable services across the stack, collaborating with government customers and engineers.

The ideal candidate combines strong programming (Python, C/C++, Java), solid ML theory, and hands-on experience with TensorFlow/PyTorch/Caffe, plus CI/CD

Qualifications

• Bachelor's degree in Computer Science, Electrical Engineering, Statistics, or related field with ≥10 years of experience; OR M.S. with ≥8 years; OR Ph.D. with ≥5 years of relevant experience.
• Ability to obtain and maintain an active security clearance.
• Onsite work 5 days per week at SEI office in Pittsburgh, PA or Arlington, VA.
• Strong experience in Python, C/C++, and Java; production-grade code and APIs.
• Solid understanding of ML theory, statistical learning, and common algorithms.
• Hands-on experience with TensorFlow, PyTorch, Torch, Caffe, or similar deep-learning libraries.
• Familiarity with CI/CD pipelines, container orchestration (Docker/Kubernetes), model versioning, and security-focused tooling.

Responsibilities

• Design, implement, and evaluate state‑of‑the‑art ML models (computer‑vision, NLP, planning, etc.) using frameworks such as TensorFlow, PyTorch, Torch, or Caffe.
• Build and maintain robust data pipelines, ETL processes, and backend services in Python, C/C++, and Java.
• Lead rapid‑prototyping efforts, translate research results into operational prototypes, and test for performance, robustness, and security.
• Define and refine DevSecOps practices for ML (model registries, containerized deployment, continuous integration/continuous delivery, security scanning).
• Mentor junior team members, collaborate with researchers, government customers, and other engineers, and contribute to technical strategy for the lab.

Skills

Python

C/C++

Java

ML theory

TensorFlow

PyTorch

Caffe

CI/CD pipelines

Docker/Kubernetes

Security clearance

Education

B.S. in CS/EE/Statistics

M.S.

Ph.D.

Tools

TensorFlow

PyTorch

Torch

Caffe

Docker

Kubernetes

Job description

Carnegie Mellon University's SEI AI Division seeks a Machine Learning Engineer to transform research ideas into mission-ready prototypes for defense and national security applications. You will design ML models, build data pipelines, and deploy secure, scalable services across the stack, collaborating with government customers and engineers.

The ideal candidate combines strong programming (Python, C/C++, Java), solid ML theory, and hands-on experience with TensorFlow/PyTorch/Caffe, plus CI/CD