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Entrylevel Machine Learning Engineer Jobs in Manassas, VA

As a Machine Learning Engineer, you will prepare datasets, train and optimize models, and maintain and improve model inference services. You will learn and apply new techniques from open source ...

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 ...

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 ...

... 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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Entrylevel Machine Learning Engineer information

See Manassas, VA salary details

$31.5K

$128.7K

$193.5K

How much do entrylevel machine learning engineer jobs pay per year?

As of Jun 10, 2026, the average yearly pay for entrylevel machine learning engineer in Manassas, VA is $128,740.00, according to ZipRecruiter salary data. Most workers in this role earn between $101,500.00 and $155,000.00 per year, depending on experience, location, and employer.

What is the difference between Entrylevel Machine Learning Engineer vs Data Scientist?

AspectEntrylevel Machine Learning EngineerData Scientist
Required CredentialsBachelor's in CS, Math, or related; some knowledge of ML frameworksBachelor's or higher in CS, Statistics, or related; strong analytical skills
Work EnvironmentDevelops ML models, implements algorithms, collaborates with engineering teamsAnalyzes data, builds statistical models, interprets data insights
Industry UsageTech companies, startups, AI-focused firmsFinance, healthcare, marketing, research institutions

While both roles involve working with data and algorithms, an Entrylevel Machine Learning Engineer primarily focuses on developing and deploying machine learning models within software systems. In contrast, a Data Scientist emphasizes analyzing data, creating statistical models, and deriving insights. Both roles often require similar educational backgrounds, but their day-to-day tasks and industry applications differ.

What cities near Manassas, VA are hiring for Entrylevel Machine Learning Engineer jobs? Cities near Manassas, VA with the most Entrylevel Machine Learning Engineer job openings:
Machine Learning Engineer

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Job description

Machine Learning Engineer

EMI Advisors LLC (EMI Advisors) is a boutique technology and innovation advisory firm that harnesses disruptive solutions for the greater good. Our team works side-by-side with our client-partners to provide strategic, operational, and technical guidance across the health, human services, defense, and information technology sectors. We are mission-driven and energized by the opportunity to collaborate with smart, diverse, and passionate people every day. It is our privilege to design and build solutions that improve the health and well-being of individuals, communities, and societies.

EMI Advisors values candidates with a growth mindset: believing your talents can be developed through hard work, smart strategies, and input from others.

About the Role

From your first day at EMI Advisors, you will be both challenged and empowered to make a tangible impact, contributing meaningfully to client-facing projects and the long-term products that define our company. You will play an active role in shaping, refining, and expanding EMI Advisors' core software capabilities. Working closely with data scientists, software engineers, and DevOps engineers, you will help bridge the gap between machine learning models and fully operational, real-world solutions.

This role is a strong fit if you combine deep technical skills with a genuine desire to grow and stretch what you thought was possible. You are driven by outcomes and excited by the challenge of applying software engineering and data science to problems that have real consequences. You understand that delivering client-centered solutions, communicating with clarity, and building capabilities that scale and repeat are what separate good work from lasting impact.

Your day-to-day will include:

  • Developing machine learning models and custom analytic algorithms that are applied to time series, geospatial, image, video, text, and structured data.
  • Orchestrating and automating complex data engineering and analytic pipelines.
  • Envisioning, specifying, and designing and implementing the core product functionality.
  • Conducting mission-critical work in support of clients and partners.
Required Qualifications
  • BS or BA degree in Engineering, Statistics, Math, Economics, Computer Science, Data Science, Cognitive Science, or a related discipline and 2+ years of relevant experience.
  • Proven track record designing and delivering data-centric systems, spanning data engineering, data cleaning, ETL pipelines, machine learning, and production analytics.
  • Fluency in programming languages and libraries central to machine learning is required, with Python expertise being essential; working knowledge of frameworks such as TensorFlow, PyTorch, and/or scikit-learn is expected.
  • Strong foundation in software engineering fundamentals, including algorithms, data structures, and design patterns, along with proficiency in at least one systems programming language (e.g., Go, Rust, C++, Java, or Scala).
  • Hands-on experience with modern software engineering tools and practices, including Agile methodologies, version control, issue tracking, CI/CD pipelines, and debugging.
  • Eligibility and willingness to obtain and maintain a Secret (or above) U.S. security clearance.
Preferred Qualifications
  • Advanced degree (MA, PhD) in Engineering, Statistics, Math, Economics, Computer Science, Data Science, Cognitive Science, or a related discipline.
  • Familiarity with client-server architectures and relevant design patterns, including asynchronous programming, REST, GraphQL, and modern frontend frameworks such as React, Vue, or Angular.
  • Demonstrated experience deploying software into containerized or cloud-based environments, including familiarity with tools such as Docker, Kubernetes, infrastructure-as-code practices, and major cloud platforms.
  • Background working across a range of structured and unstructured data types, such as imagery, full motion video, text, acoustic, sonar, RF, and telemetry signals.
  • Experience developing agentic systems, agentic workflows, or AI agents.
  • Proven ability to define, scope, plan, and see complex technical solutions through to delivery.
  • Experience guiding or leading a small technical team.
  • Experience delivering technology solutions in secure government environments.
  • Active Secret (or above) U.S. security clearance.
Benefits and Perks
  • Flexible work schedule
  • 401(k)
  • Health benefits
  • Medical and dental insurance
  • Tuition assistance
  • Referral program
  • Paid time off

EMI Advisors is an equal opportunity employer. We prohibit discrimination and harassment of any kind. This policy applies to all employment practices within our organization, including hiring, recruiting, promotion, termination, layoff, recall, leave of absence, compensation, benefits, training, and apprenticeship. EMI Advisors makes hiring decisions based solely on qualifications, merit, and business needs at the time.