Machine Learning Engineer

Carnegie Mellon University

Pittsburgh (Allegheny County)

Presencial

USD 130.000 - 190.000

Jornada completa

Hace 6 días

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Ventajas ofrecidas por este puesto de trabajo

Comprehensive medical, prescription, 9

Retirement savings with employer match

Tuition benefits

Paid time off and holidays

Life and AD&D insurance

Free Pittsburgh Regional Transit bus p

Family Concierge for childcare

Fitness center access

Descripción de la vacante

Carnegie Mellon University’s SEI AI Division is seeking a Machine Learning Engineer to engineer secure, robust AI systems that support research into vulnerabilities in AI and ML algorithms, with an emphasis on defenses suitable for government sponsors.

In this role you will develop engineering solutions that study how AI systems can be attacked, create practical mitigations and defenses, and advance applied adversarial machine learning capabilities, while mentoring teammates and collaborating

Formación

Bachelor’s degree in computer science, statistics, machine learning, electrical engineering, or related discipline with 10 years of experience.
MS with 8 years of experience in related fields.
PhD with 5 years of experience in related fields.
Willingness to obtain DoD security clearance and work onsite in Pittsburgh or Arlington.

Responsabilidades

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 TensorFlow, PyTorch, Torch, and Caffe, with Python, C/C++, and Java.
Work with data pipelines, ETL processes, and backend systems.
Experiment with modern ML frameworks, methods, and algorithms in computer vision, NLP, planning and scheduling, and robot control.
Engineer safe, trusted, and reliable machine learning systems.
Collaborate with researchers and sponsors to understand challenges and solutions.

Conocimientos

Machine learning

Adversarial ML

Engineering practices

Communication

Educación

Bachelor’s degree in computer science, statistics, machine learning, electrical engineering, or related field

MS in related field

PhD in related field

Herramientas

TensorFlow

PyTorch

Torch

Caffe

Python

C/C++

Java

Descripción del empleo

Role focus

In this position, you will develop engineering solutions that help study how AI systems can be attacked, create practical mitigations and defenses, and advance applied adversarial machine learning capabilities.

Counter AI research

Study threat models targeting AI and ML algorithms.
Understand the behaviors of AI algorithms.
Identify weak points and design novel approaches to subvert AI and ML systems.

AI and ML algorithm defense research

Create practical mitigations and defenses for observed attacks affecting AI and ML algorithms.
Evaluate the effectiveness of defensive techniques.

Applied adversarial machine learning

Advance the state of the art in adversarial machine learning.
Develop and transition capabilities to government sponsors.

Key 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 including TensorFlow, PyTorch, Torch, and Caffe, with modern programming languages including 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 machine learning frameworks, methods, and algorithms in computer vision, natural language processing, planning and scheduling, and robot control.
Engineer safe, trusted, and reliable machine learning systems.
Conduct rapid prototyping to demonstrate and evaluate technologies in relevant environments.
Evaluate systems for performance and security and test capabilities using novel testing and analysis techniques.
Participate with developers, researchers, designers, and technical leads, collaborating with researchers and government customers to understand challenges, needs, and possible solutions.
Improve the Division’s technical capabilities through mentoring and teaching, participating in design sessions, and sharing insights across SEI.

Required qualifications

Comprehensive knowledge of machine learning; prior experience in adversarial machine learning is desirable but not required.
Demonstrated use of well-established engineering practices to solve difficult problems.
Understanding of how 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 the ability to explain complex technical ideas in lay terms.
Experience publishing written or technical artifacts describing your work.
Strong collaboration skills with colleagues and sponsors.
Ability and willingness to guide and mentor junior team members.
Education and experience: a bachelor’s degree in computer science, statistics, machine learning, electrical engineering, or a related discipline with ten (10) years of experience; OR an MS in the same fields with eight (8) years of experience; OR a PhD in the same fields with five (5) years of experience.
Subject to a background investigation and must be 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