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Today

Machine Learning Engineer

Carnegie Mellon University Pittsburgh, PA

Pittsburgh, PA

Today

Full time Artificial Intelligence Data Processing Data Science

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Job Description

Build responsible, secure, and robust AI while supporting government-focused research at Carnegie Mellon University’s SEI AI Division. This onsite role in Pittsburgh is centered on engineering solutions that help investigate vulnerabilities in AI/ML algorithms and strengthen defenses against them, with a strong emphasis on turning research into practical prototypes and capabilities.

What you’ll work on

Study threat models targeting AI and ML algorithms, understand algorithm behaviors, identify weak points, and design novel ways to subvert AI and ML systems.
Create practical mitigations and defenses for observed attacks affecting AI/ML algorithms and evaluate defensive effectiveness.
Advance applied adversarial machine learning by developing and transitioning capabilities to government sponsors.

Responsibilities

Identify and investigate emerging AI and AI-adjacent technologies.
Define and refine processes, practices, and tools for working with AI.
Design and build well-engineered prototypes of AI systems.
Transition and provide guidance on AI capabilities to government sponsors.
Build machine learning models and systems using frameworks and languages including TensorFlow, PyTorch, Torch, Caffe and Python, C/C++, and Java; work with data pipelines, ETL processes, and backend systems; work with, extend, and implement state-of-the-art machine learning methods.
Experiment with modern and emerging frameworks, methods, and algorithms across domains including computer vision, natural language processing, planning and scheduling, and robot control, with a focus on safe, trusted, and reliable machine learning systems.
Conduct rapid prototyping to demonstrate and evaluate technologies in relevant environments; evaluate systems for performance and security; test capabilities using novel testing and analysis techniques.
Collaborate with developers, researchers, designers, and technical leads; partner with researchers and government customers to understand challenges, needs, and possible solutions.
Strengthen the Division’s technical capabilities through mentoring and teaching, participation in design sessions (software and otherwise), and sharing technical insights.

Required qualifications

Comprehensive knowledge of machine learning; prior experience with adversarial machine learning is desirable (not required).
Demonstrated use of well-established engineering practices to solve difficult problems.
Ability to convert research results into functioning prototypes or capabilities.
Experience leading technical projects in novel areas with limited prior work to build upon.
Strong written and verbal communication skills, including explaining complex technical ideas in a layperson’s terms.
Experience publishing written or technical artifacts showcasing your work.
Strong collaboration skills with colleagues and sponsors.
Willingness to guide and mentor junior team members.
Education and experience: bachelor’s degree with 10 years of experience, or MS with 8 years, or PhD with 5 years (in computer science, statistics, machine learning, electrical engineering, or a related discipline).
Subject to a background investigation and able to obtain and maintain an active Department of War security clearance.
Willingness to work onsite at SEI offices in Pittsburgh, PA or Arlington, VA, 5 days per week.
Willingness to travel up to 25% of the time to locations outside of your home location.

Technologies you’ll use

TensorFlow, PyTorch, Torch, Caffe
Python, C/C++, Java
Computer vision, natural language processing, planning and scheduling, robot control

Benefits

Comprehensive medical, prescription, dental, and vision insurance
Generous retirement savings program with employer contributions
Tuition benefits
Paid time off and observed holidays
Life and accidental death and disability insurance
Free Pittsburgh Regional Transit bus pass
Access to a Family Concierge Team to help navigate childcare needs
Fitness center access

Location: Pittsburgh, PA (onsite). Position type: Staff – Regular. Work arrangement: Full-time. Pay basis: Salary.

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