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No Experience Machine Learning Data Annotation Jobs in Ashburn, 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 ... Experience in healthcare industry and working with healthcare data * Experience with cloud ...

Spear AI

Machine Learning Engineer

Washington, DC · On-site +1

Background in time-series analysis or sensor data processing * Experience with edge deployment and ... This will be at no expense to you. For resources on what goes into a security background ...

Booz Allen Hamilton

Machine Learning Engineer

Arlington, VA · On-site

$77K - $176K/yr

Machine Learning Engineer The Opportunity: As an experienced AI and ML engineer, you know that ... Experience with data handling and model development * Experience leveraging AI productivity tools ...

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All JobsMachine Learning Data Annotation JobsNo Experience Machine Learning Data Annotation JobsNo Experience Machine Learning Data Annotation Jobs in Ashburn, VA

No Experience Machine Learning Data Annotation information

See Ashburn, VA salary details

$38.3K

$125.5K

$200.9K

How much do no experience machine learning data annotation jobs pay per year?

As of Aug 14, 2026, the average yearly pay for no experience machine learning data annotation in Ashburn, VA is $125,513.00, according to ZipRecruiter salary data. Most workers in this role earn between $100,700.00 and $139,100.00 per year, depending on experience, location, and employer.

What should I expect when collaborating with machine learning engineers as a data annotator with no prior experience?

As a data annotator working alongside machine learning engineers, you will play a vital role in preparing high-quality labeled data for model training. Engineers often provide clear guidelines and feedback on how to label or categorize data accurately, and they may hold regular check-ins to address questions and ensure consistency. While you may not need technical expertise, strong communication and attention to detail are essential, as your work directly impacts the performance of machine learning models. Over time, you’ll become familiar with annotation tools and may have the opportunity to take on more advanced tasks or quality assurance responsibilities.

What is a no experience machine learning data annotation job?

'No Experience Machine Learning Data Annotation' jobs are entry-level positions where individuals help label and categorize data used to train machine learning models. These roles do not require prior experience in data science or programming, making them accessible to beginners. Typical tasks may include tagging images, transcribing audio, or identifying objects in videos. These jobs are essential for improving the accuracy of AI systems and are often done remotely or on a flexible schedule.

What are the key skills and qualifications needed to thrive as a no experience machine learning data annotation specialist, and why are they important?

To succeed in a No Experience Machine Learning Data Annotation role, you need strong attention to detail, basic computer literacy, and the ability to follow precise instructions, often requiring at least a high school diploma. Familiarity with data labeling tools (like Labelbox or Supervisely) and experience with spreadsheet software are typically helpful, though many positions offer on-the-job training. Reliability, patience, and effective communication are valuable soft skills for maintaining quality and meeting deadlines. These skills ensure accurate, consistent data labeling, which is critical for training reliable machine learning models.

What is the difference between No Experience Machine Learning Data Annotation vs Data Labeling Specialist?

AspectNo Experience Machine Learning Data AnnotationData Labeling Specialist
Required CredentialsNo formal experience needed, training providedTypically similar, may require basic technical skills
Work EnvironmentRemote or office-based, repetitive tasksRemote or onsite, focused on data preparation
Industry UsageCommon in AI/ML companies, tech startupsUsed across tech, automotive, healthcare sectors
Search & Comparison IntentOften searched by beginners or entry-level job seekersCompared for skill requirements and job scope

Both roles involve labeling data for machine learning models, with minimal experience required. Data Labeling Specialists may have slightly more specialized tasks, but both are entry-level positions vital for AI development.

What are the most commonly searched types of Machine Learning Data Annotation jobs in Ashburn, VA?

The most popular types of Machine Learning Data Annotation jobs in Ashburn, VA are:

What are popular job titles related to No Experience Machine Learning Data Annotation jobs in Ashburn, VA?

For No Experience Machine Learning Data Annotation jobs in Ashburn, VA, the most frequently searched job titles are:

What job categories do people searching No Experience Machine Learning Data Annotation jobs in Ashburn, VA look for?

The top searched job categories for No Experience Machine Learning Data Annotation jobs in Ashburn, VA are:

What cities near Ashburn, VA are hiring for No Experience Machine Learning Data Annotation jobs?

Cities near Ashburn, VA with the most No Experience Machine Learning Data Annotation job openings:

No Experience Machine Learning Data Annotation jobs near you
Infographic showing various No Experience Machine Learning Data Annotation job openings in Ashburn, VA as of June 2026, with employment types broken down into 72% Full Time, and 28% Contract. Highlights an 67% In-person, and 33% Hybrid job distribution, with an average salary of $125,513 per year, or $60.3 per hour.

Machine Learning Engineer

Virtualitics, Inc

Washington, DC

Full-time

Re-posted 29 days ago

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.