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Remote Data Labelling Jobs in Washington, DC (NOW HIRING)

Maximus

Records & Document Control Specialist

VA · On-site +1

This is a remote position. Please note that this position is contingent upon bid award. Essential ... data entry functions. - Arrange meetings as required. - Attend meetings and take minutes ...

Ad Hoc

Senior UX Designer

Mclean, VA · Remote

Built for a remote life Our culture, communications, and tools are built for remote work, enabling ... We partner with these agencies to build new capabilities, deliver products, establish data as a ...

GRVTY

Imagery Scientist (EO)- Expert

Falls Church, VA · On-site +1

$180K - $210K/yr

Data formats * APIs and ETL processes * Existing operational pipelines * Develop strategies to ... Labeling * Model testing * Advanced exploitation workflows * Investigate gaps in emerging EO sensor ...

Maximus

Records & Document Control Specialist

Largo, MD · Remote

... data-driven decision-making, and equitable outcomes. In this role, you will support records and ... This is a remote position. Please note that this position is contingent upon bid award. Essential ...

Maximus

Records & Document Control Specialist

Bowie, MD · Remote

... data-driven decision-making, and equitable outcomes. In this role, you will support records and ... This is a remote position. Please note that this position is contingent upon bid award. Essential ...

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All JobsRemote Data Labelling JobsRemote Data Labelling Jobs in Washington, DC

Remote Data Labelling information

See Washington, DC salary details

$52.1K

$186.9K

$275.8K

How much do remote data labelling jobs pay per year?

As of Jul 4, 2026, the average yearly pay for remote data labelling in Washington, DC is $186,899.00, according to ZipRecruiter salary data. Most workers in this role earn between $151,200.00 and $192,500.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive in the Remote Data Labelling position, and why are they important?

To thrive as a Remote Data Labelling professional, strong attention to detail, accuracy, and basic computer literacy are essential, often requiring a high school diploma or equivalent. Familiarity with data annotation platforms, labeling tools, and sometimes experience with spreadsheet or project management software are common requirements. Excellent time management, self-motivation, and the ability to follow detailed instructions help individuals excel in this largely independent role. These qualifications are vital to ensure precise, high-quality data sets that drive effective machine learning and AI model development.

What are some common challenges faced by remote data labelling professionals, and how can they be managed?

Remote data labelling professionals often encounter challenges such as repetitive tasks, maintaining focus over extended periods, and interpreting ambiguous data accurately. To manage these challenges, it helps to take regular breaks, use productivity techniques, and seek clarification from supervisors or team leads when instructions are unclear. Many companies provide detailed guidelines and offer online support channels to help remote labelers stay engaged and ensure consistency. Being proactive in communication and attentive to updates in instructions will contribute to both job satisfaction and data quality.

What is a Remote Data Labelling job?

A Remote Data Labelling job involves annotating, categorizing, or tagging data (such as images, text, or audio) to help train machine learning models. Workers typically use specialized tools to label data based on specific guidelines provided by companies. This role is performed entirely online, making it flexible and accessible from anywhere. It is commonly used in AI development for industries like autonomous vehicles, healthcare, and e-commerce.

What are popular job titles related to Remote Data Labelling jobs in Washington, DC? For Remote Data Labelling jobs in Washington, DC, the most frequently searched job titles are:
What job categories do people searching Remote Data Labelling jobs in Washington, DC look for? The top searched job categories for Remote Data Labelling jobs in Washington, DC are:
Remote Data Labelling jobs near you
Infographic showing various Remote Data Labelling job openings in Washington, DC as of June 2026, with employment types broken down into 3% Internship, 20% Full Time, 3% Part Time, 66% Contract, and 8% Nights. Highlights an 88% Physical, 3% Hybrid, and 9% Remote job distribution, with an average salary of $186,899 per year, or $89.9 per hour.
Senior Machine Learning Engineer

Senior Machine Learning Engineer

Clearview AI

Washington, DC • On-site, Remote

$180K - $250K/yr

Full-time

Medical, Dental, Vision, Retirement, PTO

Posted 7 days ago

Job description

Senior Machine Learning Engineer
Department: Engineering
Employment Type: Full Time
Location: Remote USA
Compensation: $180,000 - $250,000 / year
Description
Clearview AI is the leading provider of facial recognition technologies to US law enforcement, state, and federal agencies. Our mission is to help our users solve crimes and prevent financial fraud with the responsible use of our facial recognition software. Our company is a high-octane, fast growing startup looking to hire enthusiastic and intelligent team members to join our team. To learn more about us, and our revolutionary facial recognition technology, please visit www.clearview.ai.
Senior Machine Learning Engineer
Position Summary: We are hiring a highly technical individual contributor to push the limits of our computer vision and machine learning capabilities. This is a high-impact, hands-on role for a research-minded engineer who wants to build and ship models, not manage a team. Much of the work involves large-scale visual understanding, extracting structured signals from imagery and reasoning about the real-world context behind a photograph, but we care more about deep ML/CV ability than any one problem area and welcome strong generalists.
Responsibilities:
  • Build, train, evaluate, and deploy computer vision and multimodal models, taking them from early prototype through to production
  • Design systems that infer structured attributes and spatial context from imagery, combining learned models with geometric and heuristic reasoning
  • Train and fine-tune models on large, diverse real-world image datasets, and build the pipelines to curate and label that data at scale
  • Work with vision-language models (VLMs) and build rigorous evaluation frameworks to measure their accuracy on our tasks
  • Develop and benchmark high-performance image retrieval capabilities with embedding models and vector indexing strategies
  • Optimize models for inference latency and throughput using techniques like distillation, quantization, and GPU acceleration
  • Read current research, prototype novel algorithms from academic literature, and turn promising ideas into reliable production code
  • Implement efficient, scalable data pipelines and inference infrastructure
  • Develop high-performance tooling in ML and data engineering
  • Additional duties and responsibilities as reasonably required by the employee's supervisor or CEO

Requirements and Experience
Requirements:
  • Experience building, training, evaluating, and deploying ML models in production
  • Strong experience using PyTorch, JAX, or other deep learning frameworks to develop and optimize models
  • Strong software engineering ability to build and maintain complex systems and work with large-scale datasets
  • Ability to solve open-ended problems and quickly learn new domains
  • Comfort operating with significant ownership and autonomy, making pragmatic trade-offs between model sophistication, velocity, inference and business constraints
  • BS, MS, or PhD in Computer Science or a related technical field, or equivalent practical experience

Nice to have:
  • Experience inferring structured, real-world attributes from images
  • Experience training models on large-scale, real-world image datasets
  • Familiarity with vision-language models (VLMs)
  • Ability to digest academic literature, prototype novel algorithms, and bridge the gap between research and production code
  • Experience building LLM or VLM pipelines and the evaluation frameworks to measure their performance
  • Experience in an ML role at a growth-stage startup
  • Publications in major ML or computer vision conferences (e.g., CVPR, ICML, ICCV, WACV)

Benefits
  • Medical, Dental, Vision, STD and LTD Plans
  • FSA - Medical and Dependent Care
  • EAP and wellness programs
  • 13 Paid Holidays
  • Unlimited PTO
  • Flexible work environment - 100% remote
  • 401(k) plan

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