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Entry Level Machine Learning Engineer Jobs in Virginia

... machine learning, artificial intelligence, and computer vision * Perform rapid prototyping and enhanced development to be integrated into operational systems * Contribute your strong programming ...

Machine Learning Engineer

Arlington, VA · On-site

$110K - $160K/yr

... machine learning, artificial intelligence, and computer vision * Perform rapid prototyping and enhanced development to be integrated into operational systems * Contribute your strong programming ...

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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

Machine Learning Engineer

Kitware

Arlington, VA • Hybrid

Full-time

Posted 10 days ago


Job description

Team Description:
Kitware is a leader in advanced research and algorithm development in artificial intelligence (AI), spanning computer vision (CV), natural language processing (NLP), vision-language models (VLMs), and other generative AI technologies. Our solutions embracing AI add measurable value to government agencies, commercial organizations, and academic institutions worldwide. We have developed a deep understanding in extracting useful, actionable information from multiple data sources like images, video, metadata, audio, and text, and we recognize the need for robust, affordable solutions. We seek to advance AI, CV, and other related fields through research and development and collaborative projects that can contribute to our open source software platforms, such as XAITK, NRTK, and GeoWATCH.

About the Projects: 
Kitware’s employees have unique opportunities to interact and collaborate directly with customers, visit interesting customer sites, and participate in live field tests and demonstrations. Much of Kitware’s work involves applying state-of-the-art artificial intelligence approaches to dynamic, real-world problems. We consider the work that we do on our government contracts as one of the ways that we give back to the community. We partner with premier government R&D agencies such as DARPA, IARPA, AFRL, Army C5ISR, NOAA, and other branches of the US Government on a range of efforts, including prime contracts, SBIRs, and STTRs. In addition, we provide commercial services to companies ranging from startups to Fortune 500 companies. Kitware employs an open source business model to foster extended, collaborative communities and to provide effective, flexible, and high-quality technical solutions.
In This Position You Will:
  • Collaborate with researchers on projects related to machine learning, artificial intelligence, and computer vision 
  • Perform rapid prototyping and enhanced development to be integrated into operational systems
  • Contribute your strong programming ability and experience to develop robust solutions for real-world problems
  • Validate, optimize, and deploy advanced exploitation algorithms
  • Perform troubleshooting, bug fixes, and maintenance of existing and new code to ensure stability and robustness
Required Qualifications:
  • Bachelor's degree or Master's degree in Computer Science, Electrical and Computer Engineering, or related field
  • Proficiency in Python
  • Experience with deep learning libraries (PyTorch, TensorFlow, etc.)
  • Strong background in both classical and modern (deep learning) machine learning, including model selection, architecting, training, validation, testing, and deployment
  • Machine learning experience using visual data
  • Understanding of a variety of machine learning tasks, e.g. Object Detection, Segmentation, Re-Identification, Tracking, Pose, Super Resolution, Natural Language Processing
  • A high level of comfort with academic literature and the ability to adapt research products to solve real-world problems
  • Due to contractual requirements, only US Citizens will be considered for this position
  • If not already cleared TS/SCI, willingness and ability to apply for and maintain a TS/SCI security clearance
  • Some travel is required, typically 5-25%
  • Willingness to work 2-5 days a week on-site in a National Capital Region area government office, with the remainder of time in Kitware's office
Preferred Qualifications:
  • Active SECRET, TS, or TS/SCI security clearance
  • Experience curating quality, real-world datasets for training deep learning models
  • Proficiency in C++
Company Description:
Kitware is a research and development software solutions provider with a mission to advance science, make a positive impact, and share our results all within a collaborative, employee-focused work environment that is friendly, fair, and flexible. Our work is improving healthcare outcomes, increasing national security, and advancing our national computing infrastructure. Our customers and collaborators include top universities from around the world, government organizations, national research labs, medical device manufacturers, car manufacturers, financial institutions, and many others.  

Kitware is proud to be 100% employee-owned, and Great Place to Work-Certified™.  

Additional Information:
Our team members enjoy a small company environment, flexibility in work assignments, and high levels of independence and responsibility. Besides a great work environment, our comprehensive benefits package includes a competitive compensation plan, tuition reimbursement program, flexible working hours, six weeks paid time off, 401(k), health insurance, life insurance, short- and long-term disability insurance, bonus plan, and free coffee, drinks, and snacks. 

For more information on our benefit offerings please visit: https://www.kitware.com/careers/.

Kitware actively subscribes to a policy of equal employment opportunity. All qualified applicants will receive consideration for employment without regard to race, color, religion, national origin, sex, age, protected veteran status, uniformed service member status, or any other characteristics protected by applicable law. 

Any unsolicited resume sent to Kitware, including to Kitware's mailing addresses, fax machines or email addresses, whether directly to Kitware employees or to Kitware's applicant tracking system, will be considered Kitware property.  Kitware will not pay a fee for any placement resulting from the receipt of an unsolicited resume, and will consider any candidate submitted by a recruitment agency without a fully executed contract with Kitware to have been referred free of any charges or fees.

If you need assistance with applying or interviewing for a role due to a disability or special need, please reach out directly to our HR team at hr@kitware.com at any time during the hiring process.  

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.