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Entry Level Machine Learning Engineer Jobs in Arlington, VA

Somatus, Inc.

Machine Learning Engineer

Mclean, VA · On-site

$105K - $115K/yr

As a Machine Learning Engineer at Somatus, you will work collaboratively with our data and technology teams to help clinical, operational, and financial partners solve advanced analytical problems.

Kitware

Machine Learning Engineer

Arlington, VA · Hybrid

$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 ...

Kitware

Machine Learning Engineer

Arlington, VA · Hybrid

$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 ...

Kitware

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 ...

J5 Consulting

Machine Learning Engineer

Herndon, VA · On-site

$117K - $141K/yr

They are seeking a Machine Learning Engineer to provide analytical support for compliance with Federal data standards, data cleansing, transformation, and data migration planning. Responsibilities ...

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Entry Level Machine Learning Engineer information

See Arlington, VA salary details

$34.5K

$79.8K

$135.8K

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

As of Jul 18, 2026, the average yearly pay for entry level machine learning engineer in Arlington, VA is $79,798.00, according to ZipRecruiter salary data. Most workers in this role earn between $59,200.00 and $90,300.00 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 Arlington, VA? The most popular types of Machine Learning Engineer jobs in Arlington, VA are:
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What cities near Arlington, VA are hiring for Entry Level Machine Learning Engineer jobs? Cities near Arlington, VA with the most Entry Level Machine Learning Engineer job openings:
Entry Level Machine Learning Engineer jobs near you
Infographic showing various Entry Level Machine Learning Engineer job openings in Arlington, VA as of July 2026, with employment types broken down into 1% Locum Tenens, 84% Full Time, 8% Part Time, 2% Temporary, and 5% Contract. Highlights an 85% Physical, 4% Hybrid, and 11% Remote job distribution, with an average salary of $79,798 per year, or $38.4 per hour.
Machine Learning Engineer

Machine Learning Engineer

Virtualitics, Inc

Washington, DC • On-site

Full-time

Re-posted yesterday

Job description

Virtualitics is the category leader in AI-native readiness applications for defense, government, and critical infrastructure. Founded on a decade of Caltech research in partnership with NASA/JPL, we are led by scientists, strategists, and servicemembers united by a single mission: to solve the world’s most complex, mission-critical challenges with AI. 

Our Readiness AI solutions deliver operational certainty — giving leaders and operators a clear picture of what’s ready, what’s at risk, and what to do next. By identifying risks early, diagnosing root causes, and recommending prioritized actions with transparent, explainable AI, we help organizations move from data complexity to decision advantage. 

Behind that impact is relentless innovation. Inventors at heart, we hold 15+ U.S. patents and are leading the shift toward agent-driven readiness. But what truly sets us apart is our culture — relentless about results, grounded in transparency, and driven by compassion for the mission and the people it serves.

If you’re motivated by impact, inspired by technical depth, and ready to build AI that performs where it matters most — you’ll find your mission here.

 
Machine Learning Engineer - US TS/SCI Clearance (DC Metropolitan Area)
 
Virtualitics is trailblazing Intelligent Exploration and Enterprise AI with our cutting-edge AI Platform. We are hiring an ML Engineer with the capability and readiness to obtain a U.S.-government security clearance. This role is pivotal in bridging the worlds of machine learning, data engineering, and software development to enhance our AI data applications. Career advancement opportunities are available for those interested
in senior engineering positions and technical leadership.
 

As an ML Applications Engineer, you will:

  • Spearhead platform upgrades, ensuring our products are at the forefront of innovation and effectiveness.

  • Craft and manage dynamic dashboards using the Virtualitics AI Platform Python SDK, transforming data into intuitive visuals for decision-making.

  • Optimize data access patterns, enhancing the efficiency and performance of our AI solutions.

  • Tackle runtime performance issues, ensuring high responsiveness and stability of applications.

  • Architect robust, scalable, and user-friendly applications, considering current trends and future growth.

  • Collaborate closely with Technical Product Managers to drive usability enhancements, ensuring our products meet and exceed user expectations.

Requirements:

  • A degree in Computer Science or related field, or 4+ years of software engineering experience.

  • Must have a TS/SCI security clearance.

  • Must be willing to travel and work from a SCIF as needed.

  • Proven track record of deploying software into production environments.

  • Proficiency in Python with a solid understanding of Python Data Stack (pandas, NumPy, scikit-learn, PyTorch, Matplotlib, etc.).

  • Experience with big data technologies and frameworks (Spark, Databricks, Snowflake, etc).

  • Familiarity with Docker, Kubernetes, and Git.

  • Exceptional problem-solving skills and a keen sense of ownership.

  • Excellent communication skills in English, both written and verbal.

Pluses:

  • Experience in Machine Learning Engineering roles and the end-to-end lifecycle of AI applications, from model development to deployment.

  • Experience with Predictive Maintenance, Supply Chain, Scheduling Optimization, etc.

  • Experience with PCAP and network monitoring, CVEs and Cyber Vulnerabilities, etc. 

  • 1 year of experience with technologies like task schedulers (e.g. Celery, Airflow, Prefect, etc.) and web-app development stacks (e.g. Flask/Django) or app building kits like Streamlit/Plotly Dash.

Compensation and Benefits:

  • Competitive salary/equity/bonus based on experience and education.

  • Comprehensive benefits package including medical, dental, and vision.

  • Unlimited paid time off.

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.