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Machine Learning Engineer Opt Jobs in Arlington, VA

Machine Learning Engineer

Ashburn, VA · On-site

$110 - $170/hr

We are seeking a Machine Learning Engineer to join our team and support our client in Ashburn, VA. The ideal candidate will bring hands‑on experience in machine learning, advanced analytics, and ...

Machine Learning Engineer

Arlington, VA · On-site

$77K - $176K/yr

R0245170 Machine Learning Engineer The Opportunity: As an experienced AI and ML engineer, you know that machine learning is critical to understanding and processing massive datasets. Your ability to ...

Machine Learning Engineer

Arlington, VA · On-site

$77K - $176K/yr

R0245828 Machine Learning Engineer The Opportunity: As an experience d AI and ML engineer, you know that machine learning is critical to understanding and processing massive datasets. Your ability to ...

We are seeking a Machine Learning Engineer to join our team and support our client in Ashburn, VA. The ideal candidate will bring hands-on experience in machine learning, advanced analytics, and AI ...

Showing results 41-60

Machine Learning Engineer Opt information

See Arlington, VA salary details

$36.2K

$148.1K

$222.6K

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

As of Aug 20, 2026, the average yearly pay for machine learning engineer opt in Arlington, VA is $148,143.00, according to ZipRecruiter salary data. Most workers in this role earn between $116,800.00 and $178,300.00 per year, depending on experience, location, and employer.

What is a machine learning engineer?

Machine Learning Engineers are specialized software engineers who design, build, and deploy machine learning models into production environments. They work at the intersection of software engineering and data science, transforming data-driven prototypes into scalable, reliable systems that organizations can use to make predictions or automate tasks. Their responsibilities include data preprocessing, choosing appropriate algorithms, model training, and ensuring the model's performance in real-world applications. Machine Learning Engineers often collaborate with data scientists, data engineers, and product teams to deliver intelligent solutions.

What are some common challenges machine learning engineers face when deploying models to production environments?

Machine Learning Engineers often encounter challenges such as ensuring model scalability, handling data drift, and integrating models seamlessly with existing systems when deploying to production. Monitoring model performance in real time and retraining models as new data becomes available are also critical tasks. Collaboration with data engineers and DevOps teams is essential to address infrastructure and deployment hurdles while maintaining model accuracy and reliability.

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

To thrive as a Machine Learning Engineer, you need a solid background in mathematics, statistics, and programming (especially Python), typically supported by a degree in computer science, engineering, or a related field. Familiarity with machine learning frameworks (such as TensorFlow, PyTorch), data processing tools, and cloud platforms, along with relevant certifications, is highly valuable. Strong problem-solving ability, collaboration, and effective communication are standout soft skills in this role. These skills and qualities ensure the successful development, deployment, and integration of machine learning solutions that drive business value.

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

AspectMachine Learning Engineer OptData Scientist
Required CredentialsBachelor's or Master's in CS, AI, or related fields; certifications in ML toolsBachelor's or Master's in CS, Statistics, or related fields; data analysis certifications
Work EnvironmentDevelops, tests, and deploys ML models in production systemsAnalyzes data, builds models, and provides insights for decision-making
Employer & Industry UsageTech companies, AI startups, e-commerce, financeResearch institutions, tech firms, consulting, finance
Common Search & ComparisonOften compared for technical skills and deployment focusCompared for data analysis and business insights

Machine Learning Engineers Opt focus on deploying scalable ML models in production environments, while Data Scientists primarily analyze data and develop models for insights. Both roles require strong technical skills, but their core responsibilities differ in application and deployment.

What are popular job titles related to Machine Learning Engineer Opt jobs in Arlington, VA?

For Machine Learning Engineer Opt jobs in Arlington, VA, the most frequently searched job titles are:

What job categories do people searching Machine Learning Engineer Opt jobs in Arlington, VA look for?

The top searched job categories for Machine Learning Engineer Opt jobs in Arlington, VA are:

What cities near Arlington, VA are hiring for Machine Learning Engineer Opt jobs?

Cities near Arlington, VA with the most Machine Learning Engineer Opt job openings:

Infographic showing various Machine Learning Engineer Opt job openings in Arlington, VA as of August 2026, with employment types broken down into 1% As Needed, 74% Full Time, 23% Part Time, and 2% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $148,143 per year, or $71.2 per hour.

Machine Learning Engineer

Unissant

Ashburn, VA • On-site

$110 - $170/hr

Other

Posted 16 days ago


Job description

Unissant, Inc. delivers innovative capabilities to the agencies that keep our nation healthy and safe. We apply our domain expertise, data acumen, and technology know-how to achieve breakthrough results for our clients. Working collaboratively, we advance missions and careers through a focus on honesty, integrity, and dependability. We continuously look for talent, excited to join that effort. To learn more about our exciting organization, please visit us at www.unissant.com .

We are seeking a Machine Learning Engineer to join our team and support our client in Ashburn, VA. The ideal candidate will bring hands‑on experience in machine learning, advanced analytics, and AI‑driven product development, with the ability to turn complex data into practical, mission‑focused solutions. This role is well suited for a technically strong professional who enjoys building and improving models, partnering across Agile teams, and supporting the delivery of innovative capabilities from early concept through deployment and ongoing performance optimization.

Essential Duties and Responsibilities:
  • Design, develop, and maintain machine learning models that support a variety of AI applications.
  • Analyze large and complex datasets to identify trends, test hypotheses, and generate actionable insights using statistical and analytical methods.
  • Build and support reliable data pipelines that improve data quality, accessibility, and usability for machine learning and analytics initiatives.
  • Collaborate with data engineering and cross‑functional teams to enhance data workflows and optimize supporting infrastructure.
  • Contribute to AI product development activities across the lifecycle, including prototyping, implementation, deployment, and post‑production support.
  • Monitor model effectiveness and product performance metrics, and perform ongoing enhancements to improve accuracy, scalability, and reliability.
  • Work closely with product managers, developers, designers, and QA teams within a large Agile development environment.
Work Experience and Job Skills:
  • Three (3) to four (4) years of hands‑on experience in machine learning engineering, AI solution development, data analytics, or related technical work is preferred.
  • Experience supporting AI, machine learning, or advanced analytics initiatives is required.
  • Demonstrated experience developing and deploying AI/ML models in a production environment.
  • Proficiency in Python, R, Java, or similar programming languages used for machine learning and analytics development.
  • Experience with machine learning libraries and frameworks such as TensorFlow, PyTorch, or Scikit‑learn.
  • Familiarity with MLOps practices, CI/CD pipelines, and model deployment processes.
  • Working knowledge of SQL and NoSQL databases and data processing tools such as Apache Spark or Hadoop.
  • Experience with analytics and visualization tools such as Tableau, Power BI, matplotlib, or Plotly.
  • Exposure to cloud platforms such as AWS, Azure, or GCP for model deployment, storage, or related services is preferred.
  • Strong problem‑solving abilities, attention to detail, and organizational skills.
  • Ability to manage multiple assignments independently while collaborating effectively across technical and business teams.
  • Experience working in Agile product development environments is a plus.
Education:
  • Bachelor's Degree in Computer Science, Data Science, Electrical Engineering, Physics, or a related technical field is required.
  • Master's Degree in a relevant field is preferred.
  • Equivalent combination of education and experience may be considered in lieu of strict degree requirements, based on client standards.
Certificates, Licenses and Registrations:
  • Relevant certifications in cloud computing, machine learning, data science, or data engineering are a plus.
  • Additional technical certifications may be considered based on program requirements.
Communication Skills:
  • Excellent verbal and written communication skills, with the ability to clearly explain technical concepts to both technical and non‑technical audiences.
  • Strong interpersonal skills and the ability to collaborate effectively across cross‑functional teams in a client‑facing environment.
Clearance Requirements:
  • Ability to obtain and maintain a Public Trust position and favorable suitability determination based on a CBP background investigation is required.
Travel:
  • This is a hybrid position based in Ashburn, VA, with onsite support expected one to two days per week and additional onsite presence as required by mission needs.
  • Mainly a routine office environment.
  • May be required to lift up to ten (10) pounds.
  • Flexible in working extended hours.

The above statements are intended to describe the general nature and level of work being performed by the individual(s) assigned to this position. They are not intended to be an exhaustive list of all duties, responsibilities, and skills required. Unissant management reserves the right to modify, add, or remove duties and to assign other duties as necessary. In addition, where applicable and available, reasonable accommodation(s) may be made to enable individuals with disabilities to perform essential functions of this position.

Please note: Candidate(s) will be required to go through pre‑employment screening.

Unissant, Inc. is a proud Equal Opportunity Employer! (EOE; M/F/Disability/Vets)

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