Associate Machine Learning Chemistry Jobs in Virginia

At the SEI AI Division, we conduct research in applied artificial intelligence and the engineering questions related to the practical design and implementation of AI technologies and systems. We currently lead a community-wide movement to mature the discipline of AI Engineering for Defense and National Security.

As our government customers adopt AI and machine learning toprovideleap-ahead mission capabilities, we

• build real-world, mission-scale AI capabilities through solving practical engineering problems

• discover and define the processes, practices, and tools to support operationalizing AI for robust, secure, scalable, and human-centered mission capabilities

• prepare our customers to be ready for the unique challenges of adopting, deploying, using, andmaintainingAI capabilities

• identifyand investigate emerging AI and AI-adjacent technologies that are rapidly transforming the technology landscape
  

Are you creative, curious, energetic, collaborative, technology-focused, and hard-working? Are you interested in making a difference by bringing innovation to government organizations and beyond? Apply to join our team.

Overview:As an Associate Machine Learning Engineer,you will specialize in engineering solutions that supportresearchinto the vulnerabilities of AIandML algorithms and securing against those vulnerabilities.

TheSecure AILab within the SEI's AI Division focuses on improving the security and robustness of AI systems. As part of the world-class research community at Carnegie Mellon University, theSecure AILabconducts and appliescutting-edgeresearch toprotectAI systems fromadversaries who aim to manipulatethe systemto learn, do, or revealsomething itisn'tsupposed to.

TheSecure AILab consists of machine learning research scientists, machine learning engineers, and software developers who work together to solve problems in the following areas:

• Counter AI Research:Study threat modelstargeting AIandML algorithms,understand the behaviors of AI algorithms,identifyweak points, and design novel ways to subvert AIandMLsystems.

• AIandMLAlgorithm DefenseResearch:Createpractical mitigations and defenses forobservedattacksaffecting AIandML algorithmsand evaluate the effectiveness ofdefensivetechniques.

• Applied Adversarial Machine Learning:Advance the state of the art in adversarial machine learning by developing and transitioning capabilities to government sponsors.

As an engineer, you will solve problems for government sponsors by analyzing, designing, and building responsible AI systems.

Your day-to-day engineering tasks will include:

• Identifyingandinvestigatingemerging AI and AI-adjacent technologies.

• Defining andrefiningprocesses, practices, and tools for working with AI.

• Designing andbuildingwell-engineered prototypes of AI systems.

• Transitioning andprovidingguidance onAI capabilities to government sponsors.

Duties

• Building Machine Learning Models and Systems:You will work with machine learning frameworks such as TensorFlow,PyTorch, Torch, and Caffe and modern programming languages including Python, C/C++, and Java. You will build and work with datapipelines, ETL processes, and backend systems. You will work with, extend, and implementstate-of-the-artmachine learning methods.

• Technical Experimentation:You will experiment with modern and emerging machine learning frameworks, methods, and algorithms in application domains that include computer vision, natural language processing,planningand scheduling, robot control, and engineering safe, trusted, and reliable machine learning systems.

• Testingand evaluation.You'llconduct rapid prototyping todemonstrateand evaluate technologies in relevant environments.You'llevaluate systems for performance and security.You'lltest capabilities using novel testing and analysis techniques.

• Collaboration.You'llactivelyparticipateon teams of developers, researchers, designers, and technical leads.You'llcollaborate with researchers and our government customers to understand challenges, needs, andpossible solutions.

• Mentoring.You'llcontribute to improving the overall technical capabilities of the Division by mentoring and teaching others,participatingin design (software and otherwise) sessions, and sharing insights and wisdom across the SEI.

Knowledge andExperience

• Comprehensiveknowledge ofmachine learning;previousexperiencein adversarial machine learningdesirablebut notrequired

• A track recordofusingwell-establishedengineering practices to solvedifficult problems

• An understanding ofhow toconvertresearch resultsintofunctioning prototypesor capabilities

• Experienceleadingtechnicalprojectsinnovelareaswith limitedpreviouswork to build upon

• Strong written and verbal communication skills;able to convey complex technical ideasinalayperson's terms

• Ampleexperience with publishingwritten or technicalartifactsshowcasingyour work

• Strong collaboration skills for working with colleagues and sponsors

• Willingnesstoguide andmentorjunior team members

Requirements

• A bachelor's degree in computer science, statistics, machine learning, electrical engineering, or related discipline with three (3) years of experience; OR MS in the same fields with one (1) year of experience; OR PhD in a relevant discipline.
  

• Willingness to work onsite 5 days per week at SEI offices in Pittsburgh, PA or Arlington, VA.

• You will be subject to a background investigation and must be able to obtain andmaintainan active Department of War security clearance.
  

• Willing to travel up to 25% of the time to locations outside of your home location. Travel sites include SEI offices in Pittsburgh and Washington, D.C., sponsor sites, and conferences.

Location

Job Function

Position Type

Full time/Part time

Pay Basis

• Please visit "Why Carnegie Mellon" to learn more about becoming part of an institution inspiring innovations that change the world.

• Click here to view a listing of employee benefits

• Carnegie Mellon University is an Equal Opportunity Employer/Disability/Veteran.

• Statement of Assurance