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Entry Level Machine Learning Jobs in Arlington, VA

Pwc

AML/Sanctions- Data Scientist- Associate

Washington, DC · On-site

$63K - $140K/yr

... machine learning, NLP, and LLMs in relevant projects - Contribute to team efforts while enhancing ... PwC does not intend to hire experienced or entry level job seekers who will need, now or in the ...

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SynergisticIT

Junior Data Analyst

Washington, DC · On-site

Currently, We are looking for entry-level software programmers, Java Full stack developers, Python/Java developers, Data analysts/Data Engineers/ Data Scientists, Machine Learning engineers for ...

MANTECH

Junior Test Engineer

Washington, DC · Hybrid

Provide entry-level technical support for Test and Evaluation of advanced and innovative ... Machine Learning agents meet baseline performance thresholds * Apply established practices to help ...

Kearney & Company

Data Analyst

Alexandria, VA · On-site

$62K - $85K/yr

This position is a great entry-level opportunity for new graduates who want hands-on dynamic ... robotics and machine learning. • Ability to learn new programming languages quickly. • ...

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Entry Level Machine Learning information

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How much do entry level machine learning jobs pay per hour?

As of Aug 13, 2026, the average hourly pay for entry level machine learning in Arlington, VA is $20.09, according to ZipRecruiter salary data. Most workers in this role earn between $17.98 and $21.83 per hour, depending on experience, location, and employer.

What types of projects can an entry level machine learning professional expect to work on in their first year?

As an entry-level machine learning professional, you’ll typically start by supporting more senior data scientists and engineers with tasks such as data cleaning, exploratory data analysis, and building baseline models. You may work on pilot projects like developing recommendation systems, automating simple classification tasks, or contributing to model evaluation and performance tuning. Collaboration with cross-functional teams—including software engineers, product managers, and domain experts—is common, providing valuable exposure to real-world business problems and laying a foundation for more complex responsibilities as you gain experience.

How to get into entry level machine learning with no experience?

Entry level machine learning roles typically require foundational knowledge in programming, statistics, and data analysis. Gaining skills through online courses, practicing with projects, and learning tools like Python, TensorFlow, or scikit-learn can help build a portfolio; internships or entry-level positions can provide practical experience.

What are the key skills and qualifications needed to thrive as an entry level machine learning engineer, and why are they important?

To thrive as an Entry Level Machine Learning Engineer, you need a solid background in mathematics, statistics, and programming (especially in Python), typically supported by a degree in computer science or a related field. Familiarity with machine learning frameworks like TensorFlow or PyTorch, version control systems like Git, and data analysis libraries is commonly required. Strong problem-solving abilities, curiosity, and effective communication skills help differentiate candidates in collaborative and fast-evolving environments. These skills and qualifications are essential for building, testing, and improving machine learning models that drive innovation and business value.

What is the difference between Entry Level Machine Learning vs Data Analyst?

AspectEntry Level Machine LearningData Analyst
Required CredentialsBachelor's in CS, Math, or related; some knowledge of programming and statisticsBachelor's in Statistics, Math, or related; proficiency in Excel, SQL, and data visualization tools
Work EnvironmentTech companies, startups, research labs; focus on developing models and algorithmsBusiness, finance, marketing; focus on interpreting data and generating reports
Employer & Industry UsageTech, e-commerce, healthcare; roles involve building predictive modelsRetail, finance, consulting; roles involve analyzing data trends and insights

Entry Level Machine Learning roles focus on developing algorithms and models using programming and statistical skills, often in tech-driven environments. Data Analysts interpret and visualize data to support business decisions, typically using tools like Excel and SQL. While both roles require analytical skills, Machine Learning positions emphasize coding and model development, whereas Data Analysts focus on data interpretation and reporting.

What are entry level machine learning jobs?

Entry-level machine learning jobs focus on creating and using software for the development of artificial intelligence (AI). In this role, you may help program computer software, engineer mechanical solutions, help develop learning objectives, and use analytics to determine whether or not the technology created is meeting development goals. Many entry-level machine learning jobs focus on particular parts of the industry. For example, some companies focus on surveillance and intelligence, while others are creating technology for self-driving vehicles. Employers often use this position as a type of extended learning period to help you develop your skills before you start taking responsibility for major projects.

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Entry Level Machine Learning jobs near you
Infographic showing various Entry Level Machine Learning job openings in Arlington, VA as of August 2026, with employment types broken down into 1% As Needed, 72% Full Time, 23% Part Time, 1% Temporary, and 3% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $41,792 per year, or $20.1 per hour.

Entry level_New graduates (Computer Science/CIS)

Dev Talent Network

Reston, VA • On-site

Full-time

Re-posted 19 days ago

Job description

Dev's Talent Network is designed to create a network of talented applicants who are interested in working for Dev Technology and are waiting for a job opening that matches their skills and experience. Here you will find positions we are "always recruiting" as well as an opportunity to share your resume with Dev, even if the job position you seek is not listed here today.
The Dev Talent Network is a community of highly qualified technical and management professionals recognized by Dev to demonstrate strong alignment with our company culture. The Dev Talent Network is comprised of candidates, referrals, Dev alumni, and fellow colleagues with whom we have worked in the past.
We're excited to evolve the Dev Talent Network so our members stay connected with Dev and discover new career opportunities with us.
Dev Technology Group frequently hires new graduates for our entry level opportunities. Dev Technology is a great place to launch your career with a variety of programs that support our new hires and growth that include our mentorship programs, Denizens, Dev University and more. We hire entry level talent in the following IT service areas: Application Development (Full Stack), QA/Testers, Business Analysts, and AI/Data Science.
Required Education, Experience, and Skills:
  • Bachelors degree in Computer Science, CIS, AI, Data Science or similar program of study
  • Demonstrated a strong interest in software development or related technical areas through past employment or academic/personal projects (e.g. GitHub portfolio, etc.) and software development concepts ad best practices for Developer and Business Analyst Opportunities
    • OR Knowledge of machine learning and data science approaches and applications for Data Science and AI Opportunities
  • Ability to obtain a U.S. government clearance as required
  • Previous internship experience learning skills applicable to Dev Technology's service areas
  • A desire to serve government clients and support their missions
  • Ability to quickly absorb and learn application functionality well enough to explain it to someone else
  • Understanding of application technology stacks and how they function together
  • Demonstrated ability to communicate clearly and concisely both verbally and in writing
  • Excellent diplomacy and communication skills with both clients and technical staff
  • Excels working as part of a team
  • Openness to continuous learning and receiving constructive feedback in order to improve
  • Familiarity with agile development methodologies including Scrum, Kanban, or Lean practices preferred

***By submitting your information you agree our talent recruitment team may use your contact information to reach out to you regarding new opportunities that may be applicable to your experience.

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