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Entry Level Machine Learning Engineer Jobs in Virginia

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Entry Level Machine Learning Engineer information

See Virginia salary details

$29.7K

$68.8K

$117K

How much do entry level machine learning engineer jobs pay per year?

As of Jun 20, 2026, the average yearly pay for entry level machine learning engineer in Virginia is $68,767.00, according to ZipRecruiter salary data. Most workers in this role earn between $51,100.00 and $77,800.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive in the Entry Level Machine Learning Engineer position, and why are they important?

To thrive as an Entry Level Machine Learning Engineer, you need a solid understanding of machine learning algorithms, programming languages like Python, and a degree in computer science, engineering, or a related field. Familiarity with tools such as TensorFlow, PyTorch, scikit-learn, and version control systems like Git is highly valuable, and completing online courses or certifications can further demonstrate your skills. Strong analytical thinking, attention to detail, and effective communication are important soft skills in this role. These abilities are essential because they enable you to build accurate models, work collaboratively with teams, and communicate insights to stakeholders.

What are some typical projects or tasks an Entry Level Machine Learning Engineer might work on?

As an Entry Level Machine Learning Engineer, you’ll often work on tasks such as data preprocessing, feature engineering, and assisting in training and evaluating models under the guidance of senior engineers or data scientists. You may help develop prototypes, automate data collection pipelines, and collaborate with software engineers to integrate machine learning solutions into products. Working in this role typically involves frequent collaboration in a team environment, participating in code reviews, and learning best practices for scalable model deployment. These foundational experiences are designed to build your technical expertise and set the stage for future growth within the field.

What is an Entry Level Machine Learning Engineer job?

An Entry Level Machine Learning Engineer is responsible for developing, testing, and deploying machine learning models under the guidance of senior engineers. They work with datasets, implement algorithms, and optimize model performance. Their role often involves data preprocessing, feature engineering, and collaborating with data scientists and software engineers. Strong programming skills in Python, knowledge of ML frameworks like TensorFlow or PyTorch, and an understanding of statistics and algorithms are essential. This position serves as a foundation for building expertise in artificial intelligence and data-driven decision-making.

What are the most commonly searched types of Machine Learning Engineer jobs in Virginia? The most popular types of Machine Learning Engineer jobs in Virginia are:
What cities in Virginia are hiring for Entry Level Machine Learning Engineer jobs? Cities in Virginia with the most Entry Level Machine Learning Engineer job openings:
Infographic showing various Entry Level Machine Learning Engineer job openings in Virginia as of June 2026, with employment types broken down into 11% Internship, 73% Full Time, 10% Part Time, and 6% Temporary. Highlights an 94% In-person, and 6% Remote job distribution, with an average salary of $68,767 per year, or $33.1 per hour.

Machine Learning Engineer - Secure AI Lab

Carnegie Mellon University

Arlington, VA

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 12 days ago


Carnegie Mellon University rating

8.6

Company rating: 8.6 out of 10

Based on 24 frontline employees who took The Breakroom Quiz

52nd of 538 rated colleges and universities


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 an 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 eight (8) years of experience; OR MS in the same fields with one (1) year of experience; OR PhD in a relevant discipline with two (2) years of experience.

  • 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.

Joining the CMU team opens the door to an array of exceptional benefits.

Benefits eligible employees enjoy a wide array of benefits including comprehensive medical, prescription, dental, and vision insurance as well as a generous retirement savings program with employer contributions. Unlock your potential with tuition benefits, take well-deserved breaks with ample paid time off and observed holidays, and rest easy with life and accidental death and disability insurance.

Additional perks include a free Pittsburgh Regional Transit bus pass, access to our Family Concierge Team to help navigate childcare needs, fitness center access, and much more!

For a comprehensive overview of the benefits available, explore our Benefits page.

At Carnegie Mellon, we value the whole package when extending offers of employment. Beyond credentials, we evaluate the role and responsibilities, your valuable work experience, and the knowledge gained through education and training. We appreciate your unique skills and the perspective you bring. Your journey with us is about more than just a job; it's about finding the perfect fit for your professional growth and personal aspirations.

Are you interested in an exciting opportunity with an exceptional organization?! Apply today!

Location

Arlington, VA, Pittsburgh, PA

Job Function

Software/Applications Development/Engineering

Position Type

Staff - Regular

Full Time/Part time

Full time

Pay Basis

Salary

More 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


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