Machine Learning Engineer

Carnegie Mellon University

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Work type
On-site
Location
Pittsburgh, PAArlington, VA
Employment
Full-time
Posted
2 days ago
Freshness
Confirmed live today
Nearby
99+ roles within 25 mi

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How this pay compares to similar roles

Similar $226k
$163k $290k
below market most similar roles pay here above market

This listing doesn't post a salary. Most similar roles pay $198,000–$254,750.

Based on 240 similar postings.

Employer

About Carnegie Mellon University

Carnegie Mellon University is a leading private research university in Pittsburgh, Pennsylvania, internationally recognized for programs in computer science, engineering, business, the arts, and artificial intelligence. Industry: Higher Education & Research

Carnegie Mellon University currently has 80 open roles on FindRole.

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At a glance

TL;DR · Machine Learning Engineer

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As a Machine Learning Engineer within the Secure AI Lab at the SEI AI Division, you will join a team of research scientists and software developers dedicated to improving the security and robustness of artificial intelligence systems. You will solve practical engineering problems by designing and building well-engineered prototypes, data pipelines, and backend systems to protect against adversarial threats. Your daily work involves identifying emerging technologies, refining operational processes, and transitioning capabilities to government sponsors. You will utilize frameworks such as TensorFlow, PyTorch, Torch, and Caffe alongside Python, C/C++, and Java. The role focuses on applied adversarial machine learning, specifically addressing vulnerabilities in computer vision, natural language processing, planning and scheduling, and robot control to ensure the development of safe, trusted, and reliable mission-scale AI capabilities.

What does a Machine Learning Engineer earn?

Median $231150 from 318 postings across 48 companies.

See salary data

Skills

Machine Learning Python PyTorch TensorFlow C/C++ Java Adversarial Machine Learning Computer Vision Natural Language Processing ETL Data Pipelines Caffe Torch Prototyping Backend Systems

What you'll do

  • Build real-world, mission-scale AI capabilities by solving practical engineering problems.
  • Design and build well-engineered prototypes of AI systems using frameworks like TensorFlow and PyTorch.
  • Develop data pipelines, ETL processes, and backend systems to support machine learning models.
  • Research and identify vulnerabilities in AI algorithms to create practical mitigations and defenses.
  • Conduct rapid prototyping to evaluate AI systems for performance, security, and reliability.
  • Define processes, practices, and tools to support the operationalization of secure and scalable AI.
  • Transition and provide technical guidance on AI capabilities to government sponsors.
  • Mentor junior team members and share technical insights across the division.

What we're looking for

  • Bachelor’s degree in computer science, statistics, machine learning, electrical engineering, or related discipline with experience.
  • Master’s degree in computer science, statistics, machine learning, electrical engineering, or related discipline with experience.
  • PhD in computer science, statistics, machine learning, electrical engineering, or related discipline with experience.
  • Must be able to obtain and maintain an active Department of War security clearance.
  • Comprehensive knowledge of machine learning.
  • Previous experience in adversarial machine learning (preferred).
  • Experience leading technical projects in novel areas and converting research results into functioning prototypes.
  • Proficiency with frameworks such as TensorFlow, PyTorch, Torch, and Caffe, and languages including Python, C/C++, and Java.

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