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Freelance Machine Learning Data Annotation Jobs in Silver Spring, MD

Gormat

Data Scientist 2

Annapolis Junction, MD · On-site

$99K - $114K/yr

* We are seeking a Data Scientist with a background in AI, Machine Learning (ML), and Natural Language Processing (NLP). You will triage the development of large language datasets and develop tools and ...

New

Gormat

Data Scientist 2

Annapolis Junction, MD

* We are seeking a Data Scientist with a background in AI, Machine Learning (ML), and Natural Language Processing (NLP). You will triage the development of large language datasets and develop tools and ...

New

USM

JB061715 - Data Scientist

Mclean, VA · On-site

... Develop machine learning algorithm Identify trends and business insights from data Create ... dashboards and visualization Work with stakeholders to solve business problem Present findings and ...

Gormat

Data Scientist 2

Annapolis Junction, MD · On-site

$99K - $114K/yr

* We are seeking a Data Scientist with a background in AI, Machine Learning (ML), and Natural Language Processing (NLP). You will triage the development of large language datasets and develop tools and ...

New

GRVTY

Data Scientist 2

Annapolis Junction, MD · On-site

We have varying levels of Data Scientist roles, depending on years of experience and education ... This role combines artificial intelligence and machine learning skills with a strong foundation in ...

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All JobsMachine Learning Data Annotation JobsFreelance Machine Learning Data Annotation JobsFreelance Machine Learning Data Annotation Jobs in Silver Spring, MD

Freelance Machine Learning Data Annotation information

See Silver Spring, MD salary details

$13

$22

$36

How much do freelance machine learning data annotation jobs pay per hour?

As of Jul 8, 2026, the average hourly pay for freelance machine learning data annotation in Silver Spring, MD is $22.61, according to ZipRecruiter salary data. Most workers in this role earn between $17.88 and $25.87 per hour, depending on experience, location, and employer.

What is the difference between Freelance Machine Learning Data Annotation vs Data Labeler?

AspectFreelance Machine Learning Data AnnotationData Labeler
CredentialsBasic understanding of annotation tools, sometimes with specialized domain knowledgeTypically no formal credentials required
Work EnvironmentRemote, flexible, project-basedOften remote or in-house, depending on employer
Industry UsageUsed in AI/ML development for training datasetsUsed in data preparation for various industries, including AI
Search/Comparison IntentFocuses on freelance opportunities, project scope, and toolsMore general, often employed by companies for data labeling tasks

Freelance Machine Learning Data Annotation involves independently completing annotation tasks for AI models, often with specialized tools and domain knowledge. Data Labelers typically perform similar tasks but may work as employees or contractors within a company. The main difference lies in the freelance nature and project-based work of data annotation roles.

What are the key skills and qualifications needed to thrive as a Freelance Machine Learning Data Annotation specialist, and why are they important?

To thrive as a Freelance Machine Learning Data Annotation specialist, you need attention to detail, basic knowledge of data labeling concepts, and familiarity with machine learning data types. Experience with annotation tools (such as Labelbox, RectLabel, or CVAT) and understanding of data privacy protocols are commonly required. Strong communication, time management, and the ability to follow complex guidelines are essential soft skills for delivering accurate results. These skills ensure high-quality, consistent data annotation, which is critical for effective machine learning model training and performance.

What is freelance machine learning data annotation?

Freelance machine learning data annotation involves labeling or tagging data—such as images, text, audio, or video—to help train machine learning models. As a freelancer, you work independently or through platforms, completing specific annotation tasks assigned by companies or researchers. This work is essential because high-quality labeled data is required for AI systems to learn and make accurate predictions. Annotators may categorize images, transcribe speech, or highlight relevant information in documents. The flexibility of freelancing allows you to choose projects and work remotely.

What are some common challenges faced by freelance machine learning data annotators, and how can they be managed?

Freelance machine learning data annotators often encounter challenges such as maintaining data accuracy, handling repetitive tasks, and understanding complex annotation guidelines. Staying organized and regularly reviewing project instructions can help ensure consistency and quality in annotations. Additionally, communicating proactively with project managers and utilizing annotation tools efficiently can help manage workload and clarify uncertainties. Building expertise in different data types (text, image, audio) also allows annotators to diversify their projects and reduce monotony.
What are popular job titles related to Freelance Machine Learning Data Annotation jobs in Silver Spring, MD? For Freelance Machine Learning Data Annotation jobs in Silver Spring, MD, the most frequently searched job titles are:
What job categories do people searching Freelance Machine Learning Data Annotation jobs in Silver Spring, MD look for? The top searched job categories for Freelance Machine Learning Data Annotation jobs in Silver Spring, MD are:
What cities near Silver Spring, MD are hiring for Freelance Machine Learning Data Annotation jobs? Cities near Silver Spring, MD with the most Freelance Machine Learning Data Annotation job openings:
Freelance Machine Learning Data Annotation jobs near you
Infographic showing various Freelance Machine Learning Data Annotation job openings in Silver Spring, MD as of July 2026, with employment types broken down into 2% Locum Tenens, 24% Full Time, 25% Part Time, 15% Contract, 33% Nights, and 1% Summer. Highlights an 33% Physical, 2% Hybrid, and 65% Remote job distribution, with an average salary of $47,019 per year, or $22.6 per hour.

Machine Learning Engineer, Detection and Tracking

Helsing

Washington, DC • On-site

Full-time

Medical, PTO

Posted 20 days ago

Job description

Who we are
Helsing develops artificial intelligence-enabled capabilities to protect and defend democracies. We build Altra, an AI-powered drone software platform, and HX-2, our autonomous drone. We are growing our US operations, cultivating an ambitious and committed team of mission-driven professionals to apply their skills to solve challenging problems.
The role
You will own the detection and tracking models that power Helsing's products - training, tuning, and deploying models against US-specific datasets. This is an applied ML role: you won't be writing research papers, but you will be expected to have strong intuition for model performance, data quality, and the practical trade-offs involved in getting detection and tracking systems to work reliably in production. You will manage the full model lifecycle - from assessing and curating training data through annotation, training, evaluation, and deployment to edge platforms.
The day-to-day
  • Training and fine-tuning detection models (YOLO, DETR, Faster R-CNN, and similar architectures) on mission-specific datasets
  • Implementing and improving multi-object tracking pipelines (SORT, DeepSORT, ByteTrack, or similar)
  • Evaluating model performance: analyzing metrics, diagnosing failure modes, and iterating on data and model improvements
  • Managing the data pipeline end-to-end: assessing raw data, coordinating annotation, curating datasets, and implementing augmentation strategies
  • Optimizing models for deployment on SWaP-constrained and embedded platforms (quantization, pruning, TensorRT, ONNX export)
  • Collaborating with systems engineers to integrate models into the broader Altra platform
  • Working across sensor modalities as needed, including electro-optical, infrared, and other imaging sources
You should apply if you
  • Have 5+ years of experience in applied machine learning or computer vision
  • Have a Bachelor's degree in Computer Science, Electrical Engineering, or a related field; Master's or PhD strongly preferred
  • Have production experience training and deploying object detection models - not just research or academic projects
  • Are proficient in Python and PyTorch or a comparable deep learning framework
  • Have strong intuition for data quality; you can look at annotated datasets, training curves, and evaluation metrics and know what's wrong
  • Have experience with the full model training lifecycle: data curation, annotation management, training, evaluation, and deployment
  • Have experience optimizing models for deployment on SWaP-constrained and edge platforms (TensorRT, ONNX, quantization)
  • Understand multi-object tracking and have implemented or worked with tracking algorithms in practice
  • Can read and contextualize scientific papers in computer vision and apply findings to production systems
  • Are a U.S. citizen with an active security clearance or the ability to obtain one
Nice to have
  • Strong proficiency in Rust or C++ for production model deployment and optimization
  • Experience with multiple sensor modalities - particularly infrared or thermal imaging
  • Familiarity with MLOps tooling: experiment tracking (MLflow, Weights & Biases), dataset versioning, model registries
  • Experience with annotation tools and workflows (CVAT, Label Studio, or similar)
  • Background in computer vision beyond detection - segmentation, pose estimation, activity recognition
  • Experience with simulators, emulators, or synthetic data generation for training and evaluation
  • Experience deploying models on GPU-accelerated embedded platforms (NVIDIA Jetson, similar)
  • Background in defense, intelligence, or other mission-critical environments
Join Helsing and work with world-leading experts in their fields
  • Helsing's work is important. You'll be directly contributing to the protection of democratic countries while balancing both ethical and geopolitical concerns
  • The work is unique. We operate in a domain that has highly unusual technical requirements and constraints, and where robustness, safety, and ethical considerations are vital. You will face unique Engineering and AI challenges that make a meaningful impact in the world
  • Our work frequently takes us right up to the state of the art in technical innovation, be it reinforcement learning, distributed systems, generative AI, or deployment infrastructure. The defense industry is entering the most exciting phase of the technological development curve. Advances in our field of world are not incremental: Helsing is part of, and often leading, historic leaps forward
  • In our domain, success is a matter of order-of-magnitude improvements and novel capabilities. This means we take bets, aim high, and focus on big opportunities. Despite being a relatively young company, Helsing has already been selected for multiple significant government contracts
  • We actively encourage healthy, proactive, and diverse debate internally about what we do and how we choose to do it. Teams and individual engineers are trusted (and encouraged) to practice responsible autonomy and critical thinking, and to focus on outcomes, not conformity. At Helsing you will have a say in how we (and you!) work, the opportunity to engage on what does and doesn't work, and to take ownership of aspects of our culture that you care deeply about
What we offer
  • A focus on outcomes, not time-tracking
  • A generous compensation and benefits package (in addition to base salary) that includes, but may not be limited to, insurance coverage (medical and travel), flexible paid time off, paid holidays, and remote and/or hybrid work available depending on position. All compensation and benefits are subject to the terms and conditions of the underlying plans or programs, as applicable and as may be amended, terminated or superseded from time to time.

Helsing is an Equal Opportunity Employer. We will consider all qualified applicants without regard to race, color, sex, sexual orientation, gender identity, national origin, age, disability, protected veteran status, genetics, or any other characteristic protected by applicable federal, state, or local law. Please do not submit personal data revealing racial or ethnic origin, political opinions, religious or philosophical beliefs, trade union membership, data concerning your health, or data concerning your sexual orientation.
Helsing's Candidate Privacy and Confidentiality Regime can be found here.

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