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Manager Annotation Jobs in Ashburn, VA (NOW HIRING)

AI Finance Expert - Remote

Washington, DC ยท Remote

$100 - $200/hr

Data Annotation * Problem-Solving * Independent Research * Attention to Detail Preferred ... management, or strategic finance. * Experience preparing investment memos, valuation analyses ...

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Manager Annotation information

See Ashburn, VA salary details

$25.1K

$60.9K

$118.6K

How much do manager annotation jobs pay per year?

As of Aug 23, 2026, the average yearly pay for manager annotation in Ashburn, VA is $60,871.00, according to ZipRecruiter salary data. Most workers in this role earn between $42,900.00 and $70,000.00 per year, depending on experience, location, and employer.

What is a manager annotation?

Manager Annotation jobs involve overseeing teams responsible for labeling and annotating data, which is critical for training machine learning models. These managers coordinate workflows, ensure quality control, and facilitate communication between annotators and data scientists. They are responsible for setting guidelines, managing deadlines, and addressing any issues that arise during the annotation process. Manager Annotation roles often require a combination of leadership skills and an understanding of data annotation tools and processes.

What are the key skills and qualifications needed to thrive as a manager annotation?

To thrive as a Manager Annotation, you need expertise in data annotation processes, team leadership, and quality assurance, often supported by a relevant degree and experience in data labeling or AI/ML projects. Familiarity with annotation tools (such as Labelbox, Supervisely, or AWS SageMaker Ground Truth), project management software, and sometimes certifications in project management or data science are valuable. Strong communication, problem-solving abilities, and attention to detail help ensure effective team coordination and high-quality data outputs. These skills are crucial for delivering accurate training data, meeting project deadlines, and supporting the success of machine learning initiatives.

What are some common challenges faced by a manager annotation and how can they be addressed?

A Manager Annotation often encounters challenges such as ensuring high-quality data labeling, managing tight project deadlines, and maintaining effective communication across diverse annotation teams. Balancing quality control with efficiency can be demanding, especially when working with large datasets or remote teams. To address these challenges, it is helpful to establish clear annotation guidelines, implement robust quality assurance processes, and foster open communication channels for feedback and support. Regular training and performance reviews also play a key role in maintaining team standards and project consistency.

What is the difference between Manager Annotation vs Data Annotator?

AspectManager AnnotationData Annotator
Required CredentialsHigh school diploma or equivalent; experience in data labeling; leadership skillsHigh school diploma or equivalent; attention to detail; basic computer skills
Work EnvironmentOffice or remote management setting overseeing annotation teamsRemote or on-site data labeling tasks
Employer & Industry UsageTech companies, AI firms, data service providersAI, machine learning, data processing companies

The main difference is that a Manager Annotation oversees annotation teams and manages projects, requiring leadership and management skills, while a Data Annotator performs the actual data labeling work, focusing on accuracy and attention to detail. Managers coordinate workflows, whereas Annotators execute labeling tasks.

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

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

What are popular job titles related to Manager Annotation jobs in Ashburn, VA?

For Manager Annotation jobs in Ashburn, VA, the most frequently searched job titles are:

What job categories do people searching Manager Annotation jobs in Ashburn, VA look for?

The top searched job categories for Manager Annotation jobs in Ashburn, VA are:

Machine Learning Engineer, Detection and Tracking

Helsing

Washington, DC โ€ข On-site

Full-time

Medical, PTO

Re-posted 5 days ago


Job description

Who we areย 

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.ย 

The roleย 

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.ย 

The day-to-dayย 
  • Training and fine-tuning detection models (YOLO, DETR, Faster R-CNN, and similar architectures) on mission-specific datasetsย 
  • Implementing and improving multi-object tracking pipelines (SORT, DeepSORT, ByteTrack, or similar)ย 
  • Evaluating model performance: analyzing metrics, diagnosing failure modes, and iterating on data and model improvementsย 
  • Managing the data pipeline end-to-end: assessing raw data, coordinating annotation, curating datasets, and implementing augmentation strategiesย 
  • Optimizing models for deployment on SWaP-constrained and embedded platforms (quantization, pruning, TensorRT, ONNX export)ย 
  • Collaborating with systems engineers to integrate models into the broader Altra platformย 
  • Working across sensor modalities as needed, including electro-optical, infrared, and other imaging sourcesย 
You should apply if youย 
  • Have 5+ years of experience in applied machine learning or computer visionย 
  • Have a Bachelor's degree in Computer Science, Electrical Engineering, or a related field; Master's or PhD strongly preferredย 
  • Have production experience training and deploying object detection models - not just research or academic projectsย 
  • Are proficient in Python and PyTorch or a comparable deep learning frameworkย 
  • Have strong intuition for data quality; you can look at annotated datasets, training curves, and evaluation metrics and know what's wrongย 
  • Have experience with the full model training lifecycle: data curation, annotation management, training, evaluation, and deploymentย 
  • Have experience optimizing models for deployment on SWaP-constrained and edge platforms (TensorRT, ONNX, quantization)ย 
  • Understand multi-object tracking and have implemented or worked with tracking algorithms in practiceย 
  • Can read and contextualize scientific papers in computer vision and apply findings to production systemsย 
  • Are a U.S. citizen with an active security clearance or the ability to obtain oneย 
Nice to haveย 
  • Strong proficiency in Rust or C++ for production model deployment and optimizationย 
  • Experience with multiple sensor modalities - particularly infrared or thermal imagingย 
  • Familiarity with MLOps tooling: experiment tracking (MLflow, Weights & Biases), dataset versioning, model registriesย 
  • Experience with annotation tools and workflows (CVAT, Label Studio, or similar)ย 
  • Background in computer vision beyond detection - segmentation, pose estimation, activity recognitionย 
  • Experience with simulators, emulators, or synthetic data generation for training and evaluationย 
  • Experience deploying models on GPU-accelerated embedded platforms (NVIDIA Jetson, similar)ย 
  • Background in defense, intelligence, or other mission-critical environmentsย 
Join Helsing and work with world-leading experts in their fieldsย 
  • 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. ย 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.