ZipRecruiter

Log In

2

Freelance Remote Image Annotation Jobs in Virginia

aqua IT

AI/ML Engineer (Computer Vision)

Herndon, VA · On-site +1

Experience processing and augmenting image datasets at scale * 3+ years of experience with AWS ML ... Familiarity with data annotation platforms and active learning workflows for imagery * Experience ...

All JobsFreelance Remote Image Annotation JobsFreelance Remote Image Annotation Jobs in Virginia

Freelance Remote Image Annotation information

What is the difference between Freelance Remote Image Annotation vs Freelance Remote Data Labeling?

AspectFreelance Remote Image AnnotationFreelance Remote Data Labeling
CredentialsBasic computer skills, attention to detailBasic computer skills, attention to detail
Work EnvironmentRemote, flexible hoursRemote, flexible hours
Industry UsageAI, machine learning, autonomous vehiclesAI, machine learning, natural language processing
Job FocusLabeling images with bounding boxes, polygons, or masksLabeling data for various AI models, including images, text, or audio

Freelance Remote Image Annotation primarily involves labeling images for AI training, focusing on visual data. Freelance Remote Data Labeling covers a broader range of data types, including images, text, and audio, for AI applications. While both roles require attention to detail and remote work skills, image annotation is more specialized in visual data, whereas data labeling encompasses multiple data formats.

What are the key skills and qualifications needed to thrive as a Freelance Remote Image Annotation Specialist, and why are they important?

To excel as a Freelance Remote Image Annotation Specialist, you need strong attention to detail, visual analysis skills, and a basic understanding of computer vision concepts, often supported by experience or training in data annotation. Familiarity with annotation tools like Labelbox, VGG Image Annotator, or Supervisely, as well as basic proficiency in using cloud-based platforms, is typically required. Time management, reliability, and effective written communication are crucial soft skills for meeting deadlines and collaborating remotely. These competencies ensure high-quality, accurate datasets essential for training AI models and supporting machine learning projects.

What is freelance remote image annotation?

Freelance remote image annotation involves labeling or tagging elements within images to help train artificial intelligence and machine learning models. As a freelancer, you work from home or any location, using online platforms or specialized software to mark objects, boundaries, or features within digital images according to specific guidelines. This work is essential for industries like autonomous vehicles, healthcare, and e-commerce, as annotated images enable computers to 'see' and understand visual data. Freelance image annotators typically get paid per task or project, offering flexibility and the opportunity to work with multiple clients. Attention to detail, time management, and basic computer skills are important for success in this role.

What are some common challenges faced in freelance remote image annotation, and how can they be managed effectively?

Freelance remote image annotation professionals often face challenges such as maintaining high accuracy under tight deadlines, handling repetitive tasks, and ensuring consistent internet connectivity. Managing these challenges involves developing a strong attention to detail, setting up a distraction-free workspace, and using time management tools to balance multiple projects. Regular communication with project managers and staying updated on annotation guidelines also help ensure quality and efficiency in the role.
What are the most commonly searched types of Remote Image Annotation jobs in Virginia? The most popular types of Remote Image Annotation jobs in Virginia are:
What are popular job titles related to Freelance Remote Image Annotation jobs in Virginia? For Freelance Remote Image Annotation jobs in Virginia, the most frequently searched job titles are:
What job categories do people searching Freelance Remote Image Annotation jobs in Virginia look for? The top searched job categories for Freelance Remote Image Annotation jobs in Virginia are:
What cities in Virginia are hiring for Freelance Remote Image Annotation jobs? Cities in Virginia with the most Freelance Remote Image Annotation job openings:
Freelance Remote Image Annotation jobs near you

AI/ML Engineer (Computer Vision)

aqua IT

Herndon, VA • On-site, Remote

Full-time

Posted 8 days ago

Job description

Responsibilities:

  • Design and execute fine-tuning pipelines for Vision-Language Models (VLMs) on domain-specific imagery datasets, including data preprocessing, training orchestration, and hyperparameter optimization
  • Develop and implement evaluation frameworks for multimodal model performance, including task-specific metrics for image understanding, visual question answering, and spatial reasoning
  • Build scalable training infrastructure on AWS (SageMaker, EC2 GPU instances) for distributed fine-tuning of large multimodal models
  • Engineer data pipelines for curating, annotating, and transforming geospatial imagery datasets into model-ready formats for supervised and instruction-tuning workflows
  • Collaborate with applied scientists and solutions architects to iterate on model architectures, adapter strategies (LoRA/QLoRA), and inference optimization techniques

Basic Requirements

  • TS/SCI with CI Poly required
  • 5+ years of professional machine learning engineering experience with a focus on deep learning
  • 1+ years of hands-on experience fine-tuning large foundation models (LLMs or VLMs)
  • Experience with parameter-efficient fine-tuning methods (LoRA, QLoRA, adapters)
  • Familiarity with supervised fine-tuning, instruction tuning, and RLHF/DPO alignment techniques
  • 4+ years of advanced Python development for ML workloads
  • Strong proficiency with PyTorch and the HuggingFace ecosystem (Transformers, PEFT, Datasets, Accelerate)
  • Experience with distributed training frameworks (DeepSpeed, FSDP, or Megatron)
  • 3+ years of experience with computer vision or multimodal models
  • Understanding of vision transformer architectures (ViT, CLIP, LLaVA-family models, or similar)
  • Experience processing and augmenting image datasets at scale
  • 3+ years of experience with AWS ML infrastructure
    SageMaker Training jobs, Processing jobs, and endpoint deployment
    GPU instance selection, multi-node training, and cost optimization on EC2 (P4/P5/G5/G6e), S3 data management for large-scale training datasets
  • 2+ years of experience building ML evaluation pipelines Automated benchmarking, metric computation, and result analysis
  • Experience with both quantitative metrics and qualitative/human evaluation approaches
  • Strong software engineering fundamentals (version control, testing, CI/CD for ML workflows)

Preferred Qualifications:

  • 2+ years of experience with geospatial or remote sensing imagery
  • Familiarity with electro-optical and SAR satellite imagery formats and characteristics
  • Understanding of geospatial metadata, coordinate systems, and imagery preprocessing
  • Experience with model quantization and inference optimization (vLLM, TensorRT, ONNX)
  • Experience with MLOps and experiment tracking tools (MLflow, Weights & Biases, SageMaker Experiments)
  • Familiarity with data annotation platforms and active learning workflows for imagery
  • Experience with containerized ML workflows (Docker, ECR, ECS/EKS)
  • 2+ years of experience with Authority to Operate (ATO) processes in government environments
  • Implementation of NIST 800-53 controls and security compliance for ML systems
  • Experience deploying models in air-gapped or disconnected environments
  • Familiarity with multimodal evaluation benchmarks (MMMU, MMBench, GQA, or domain-specific equivalents)
  • Publications or demonstrated contributions in computer vision, VLMs, or multimodal AI
  • Experience with synthetic data generation for training data augmentation