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Ai Annotation Jobs in Springfield, VA (NOW HIRING)

No prior AI experience is required--your coding expertise and attention to detail are what matter ... Familiarity with digital annotation tools or healthcare data projects is a plus. * Commitment to ...

New

No prior AI experience is required--your healthcare legal expertise, regulatory knowledge, and ... Legal Document Review & Annotation * Policy Analysis * Contract Drafting * U.S. Healthcare ...

New

... annotation standards, resolve taxonomy issues, and identify data-quality improvements based on model failure modes. • Independently prototype, evaluate, and deploy AI capabilities in a secure ...

... annotation to senior-annotator adjudication * Validate quality scoring and IAA computation within the Innodata data layer * Support AI Solutions Engineer on evaluation design for SAM 2 and Frontier ...

... annotation standards, resolve taxonomy issues, and identify data-quality improvements based on model failure modes. • Independently prototype, evaluate, and deploy AI capabilities in a secure ...

Showing results 21-40

Ai Annotation information

See Springfield, VA salary details

$104.7K

$138.7K

$182.4K

How much do ai annotation jobs pay per year?

As of Aug 15, 2026, the average yearly pay for ai annotation in Springfield, VA is $138,664.00, according to ZipRecruiter salary data. Most workers in this role earn between $114,700.00 and $169,200.00 per year, depending on experience, location, and employer.

What is an AI annotation?

An AI Annotation job involves labeling, tagging, or annotating data, such as images, text, or audio, to train machine learning models. Annotators help improve AI accuracy by providing high-quality, structured data that algorithms use to learn patterns. Tasks may include identifying objects in images, transcribing speech, or classifying text-based content. This job is essential for developing AI applications like self-driving cars, chatbots, and image recognition systems.

What does an AI annotation specialist do?

As an AI Annotation specialist, your typical day will involve accurately labeling, categorizing, or tagging large volumes of images, text, audio, or video data to train AI models according to project guidelines. You may work independently or as part of a team, using specialized annotation platforms and regularly reviewing your work to ensure quality and consistency. Collaboration with data scientists or project managers may be required to clarify ambiguous cases or update labeling criteria. You can expect periodic feedback and performance reviews to help refine your skills and ensure the data meets the project’s standards, making attention to detail and adaptability essential for success.

What are the key skills and qualifications needed to thrive in the AI annotation position?

To thrive as an AI Annotation professional, you need keen attention to detail, strong analytical skills, and a basic understanding of machine learning concepts, often supported by a high school diploma or relevant technical training. Familiarity with data labeling tools, annotation platforms such as Labelbox or Supervisely, and basic spreadsheet or database management is commonly required. Strong communication, time management, and the ability to maintain focus during repetitive tasks are standout soft skills. These abilities are crucial for producing high-quality, consistent data that supports the effective development and accuracy of AI models.

What job categories do people searching Ai Annotation jobs in Springfield, VA look for?

The top searched job categories for Ai Annotation jobs in Springfield, VA are:

What cities near Springfield, VA are hiring for Ai Annotation jobs?

Cities near Springfield, VA with the most Ai Annotation job openings:

Infographic showing various Ai Annotation job openings in Springfield, VA as of August 2026, with employment types broken down into 42% Full Time, 15% Part Time, 39% Contract, and 4% Nights. Highlights an 57% In-person, and 43% Remote job distribution, with an average salary of $138,664 per year, or $66.7 per hour.

Machine Learning Engineer, Detection and Tracking Software Washington, DC

helsing.ai

Washington, DC • On-site

$100 - $130/hr

Other

Medical, PTO

Posted 9 days ago


Job description

Machine Learning Engineer, Detection and Tracking
  • Full-time
  • Washington, DC
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 are not incremental: Helsing is part of, and often leading, historic leaps forward.

In our domain, success is a matter of order‑of‑magnitudes 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.

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.

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