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Weekday Machine Learning Research Scientist Jobs in Virginia

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Weekday Machine Learning Research Scientist information

What are the key skills and qualifications needed to thrive as a Weekday Machine Learning Research Scientist, and why are they important?

To thrive as a Weekday Machine Learning Research Scientist, you need a solid background in mathematics, statistics, programming (Python, R), and a relevant advanced degree such as a Master's or Ph.D. in computer science or a related field. Expertise with machine learning frameworks (like TensorFlow, PyTorch), data processing tools, and familiarity with cloud computing platforms are typically required. Strong analytical thinking, problem-solving abilities, and clear communication skills help you collaborate with teams and present complex findings effectively. These skills are crucial for developing innovative models, delivering impactful research, and ensuring successful implementation in real-world applications.

What does a Weekday Machine Learning Research Scientist do?

A Weekday Machine Learning Research Scientist conducts research and develops new algorithms or models in the field of machine learning, typically during standard business days (Monday to Friday). Their work involves designing experiments, analyzing data, publishing findings, and collaborating with other scientists or engineers. They may focus on improving existing machine learning techniques or creating innovative solutions for real-world problems. This role often requires a strong background in mathematics, computer science, and statistics, as well as proficiency in programming languages like Python or R.

What are some common challenges faced by a Weekday Machine Learning Research Scientist, and how are they typically addressed within the team?

Weekday Machine Learning Research Scientists often encounter challenges such as managing large datasets, tuning complex models, and keeping up with rapidly evolving research. Collaboration is key—team members regularly hold meetings to share findings, brainstorm solutions, and review code. Access to robust computational resources and mentorship from senior researchers helps address technical obstacles, while a structured, weekday schedule allows for focused research and effective work-life balance.

What is the difference between Weekday Machine Learning Research Scientist vs Weekend Machine Learning Research Scientist?

AspectWeekday Machine Learning Research ScientistWeekend Machine Learning Research Scientist
CredentialsMaster's or PhD in Computer Science, Data Science, or related fieldsSame as weekday role
Work EnvironmentTypically in office or research labs during standard hoursFlexible hours, often part-time or project-based
Employer & Industry UsageTech companies, research institutions, startupsFreelance projects, consulting firms, academic collaborations

The main difference between a Weekday Machine Learning Research Scientist and a Weekend Machine Learning Research Scientist lies in their work schedule and environment. Weekday roles usually involve full-time employment with structured hours, while weekend roles are often part-time or freelance, offering more flexibility. Both roles require similar credentials and are used across tech and research industries.

What are the most commonly searched types of Machine Learning Research Scientist jobs in Virginia? The most popular types of Machine Learning Research Scientist jobs in Virginia are:

Senior Machine Learning Research Scientist - Secure AI Lab

Cmu

Arlington, VA • On-site

$105K - $143K/yr

Full-time

Posted 21 days ago


Job description

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 a Senior Machine LearningResearch Scientist,you will specialize inconductingresearch into 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 models targeting AIandML algorithms,understand the behaviors of AI algorithms,identifyweak points, and design novel ways to subvert AIandML systems.

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

  • AppliedAdversarial Machine Learning:Advance the state of the art inadversarialmachinelearningby developing and transitioning capabilities to government sponsors.

Your day-to-day research tasks will include:

  • Identifyingandinvestigatingemerging AI and AI-adjacent technologies.

  • Performing andpublishingimpactful original research in the field ofAIandML algorithm vulnerabilities and securing against those vulnerabilities.

  • Adapting andapplyingexisting research in the field to solve real-world problems.

  • Transitioning andprovidingguidanceonAI capabilities to government sponsors.

Duties:

  • Hands-on research:You'llconduct and lead novel research in applied machine learning and artificial intelligence.

  • Solution development:You'llwork with and lead interdisciplinary teams to turn research results into prototype operational capabilities for government customers and stakeholders.

  • Strategy:You'llwork withthe leadership teamand colleagues to plan, develop, and carry out an overall research strategy, and to influence the national research agendaregardingfuture technology.

  • Collaboration:You'llactivelyparticipateon teams of software developers, researchers, designers, and technical leads.You'llbuild relationships and collaborate with researchers, government customers, and other stakeholders to understand challenges, needs,possible solutions, and research directions.

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

Knowledge andExperience

  • Comprehensiveknowledge ofmachine learning;previousexperiencein adversarial machine learningpreferredbut notrequired

  • A track recordofconducting research and applying scientific methodsto solvedifficult problems

  • Experienceleadingresearchprojectsinnovelareaswith limitedpreviouswork to build upon

  • Abilityto work with leadership to plan, develop, anddeliveran overallresearchstrategy

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

  • Proficiencyinwritingfunding proposalsorpitchingideas fornew researchprojects

  • Ampleexperience with publishingwritten or technicalartifactsshowcasingyour work

  • Strong collaboration skills forworkingwith colleagues and sponsors

  • Willingnesstoguide andmentorjunior team members

Requirements

  • A bachelor's degree in computer science, statistics, machine learning, electrical engineering, or related discipline with ten (10) years of experience; OR MS in the same fields with eight (8) years of experience; OR PhD with five (5) years of experience

  • Willingness to work onsite at an SEI facility 5 days per week.

  • 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

Arlington, VA, Pittsburgh, PA

Job Function

Software/Applications Development/Engineering

Position Type

Staff - Regular

Full time/Part time

Full time

Pay Basis

SalaryMore Information:
  • 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


About CMU

Sourced by ZipRecruiter

Industry

Offices of mental health practitioners

Company size

201 - 500 Employees

Headquarters location

Harrisburg, PA, US