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Live In Image Annotation Jobs in Virginia (NOW HIRING)

NewGen Technologies Inc.

VLM Engineer

Herndon, VA · On-site

... for image understanding, visual question answering, and spatial reasoning • Build scalable ... work in SCIF daily or as needed • 5+ years of professional machine learning engineering ...

teKnoluxion

VLM Engineer

Reston, VA

Are you interested in helping to protect our nation's cyber interests? Join our growing team as a ... Experience processing and augmenting image datasets at scale * Strong software engineering ...

teKnoluxion

VLM Engineer

Springfield, VA · On-site

Are you interested in helping to protect our nation's cyber interests? Join our growing team as a ... Experience processing and augmenting image datasets at scale * Strong software engineering ...

teKnoluxion

VLM Engineer

Reston, VA

Are you interested in helping to protect our nation's cyber interests? Join our growing team as a ... Experience processing and augmenting image datasets at scale * Strong software engineering ...

Quevera LLC

Software Engineer II

Herndon, VA · On-site

$100K - $137K/yr

Employees are in control of their career path through our Career Pathway Program . Employer paid ... Experience processing and augmenting image datasets at scale * 3+ years of experience with AWS ML ...

teKnoluxion

VLM Engineer

Reston, VA · On-site

Are you interested in helping to protect our nation's cyber interests? Join our growing team as a ... Experience processing and augmenting image datasets at scale * Strong software engineering ...

Quevera LLC

Software Engineer II

Herndon, VA

$100K - $137K/yr

Employees are in control of their career path through our Career Pathway Program. Employer paid ... Experience processing and augmenting image datasets at scale * 3+ years of experience with AWS ML ...

Telus Digital

$132K - $165K/yr

... video, image, geo, and 3D data at any scale and complexity. Our data annotation capabilities ... Stay ahead of industry trends in AI training data, including emerging labeling methodologies ...

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Live In Image Annotation information

What is a Live In Image Annotation job?

A Live In Image Annotation job involves residing at a particular location or facility and performing the task of labeling or tagging objects, features, or data within digital images. This work is usually part of larger projects in fields like artificial intelligence, machine learning, or computer vision, where accurately annotated images are crucial for training algorithms. The job may require familiarity with specialized software tools and a keen attention to detail. Annotators play a critical role in helping computers 'see' and understand images by providing clear and consistent labels. Often, these positions are found in research centers, data collection facilities, or companies specializing in AI development.

What are some of the common challenges faced by Live In Image Annotation professionals, and how can they be addressed?

Live In Image Annotation professionals often encounter challenges such as maintaining high accuracy while working with large volumes of data, meeting tight deadlines, and handling ambiguous images that require careful judgment. To address these challenges, it's important to stay organized, regularly communicate with team members and project managers, and utilize annotation tools efficiently. Ongoing training and feedback can also help improve both speed and precision, ensuring the quality of annotated data meets industry standards.

What is the difference between Live In Image Annotation vs Image Labeling Specialist?

AspectLive In Image AnnotationImage Labeling Specialist
CredentialsBasic computer skills, attention to detailBasic computer skills, attention to detail
Work EnvironmentOn-site or remote, often in a dedicated workspaceRemote or on-site, flexible environment
Industry UsageAI training, autonomous vehicles, surveillanceData annotation for machine learning, AI models
Job FocusReal-time annotation, often involving live video or imagesBatch annotation, static images

Live In Image Annotation involves real-time, often on-site annotation of images or videos, suitable for applications like autonomous driving or surveillance. In contrast, Image Labeling Specialists typically perform batch annotation of static images for training AI models, often remotely. Both roles require attention to detail and basic technical skills but differ mainly in real-time versus batch work and work environment.

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

To thrive as a Live In Image Annotation Specialist, you need strong attention to detail, proficiency in visual analysis, and a basic understanding of data labeling processes, typically supported by a high school diploma or equivalent. Familiarity with annotation tools like Labelbox, CVAT, or Supervisely, and sometimes basic coding knowledge, is often required. Excellent communication, time management, and adaptability are key soft skills for collaborating and meeting project deadlines. These competencies ensure accurate, high-quality data labeling, which is crucial for training reliable machine learning models.
What are the most commonly searched types of Image Annotation jobs in Virginia? The most popular types of Image Annotation jobs in Virginia are:
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What cities in Virginia are hiring for Live In Image Annotation jobs? Cities in Virginia with the most Live In Image Annotation job openings:
Live In Image Annotation jobs near you
VLM Engineer

VLM Engineer

NewGen Technologies Inc.

Herndon, VA • On-site

Full-time

Posted 5 days ago

Job description

Job Summary:
NewGen Technologies Inc. is a company that has been solving IT challenges for over 20 years, focusing on integrity, security, and outstanding service. They are seeking a VLM Engineer to design and execute fine-tuning pipelines for Vision-Language Models on domain-specific imagery datasets, develop evaluation frameworks, and build scalable training infrastructure on AWS.
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 applies scientists and solutions architects to iterate on model architectures, adapter strategies (LoRA/QLoRA), and inference optimization techniques
Qualifications:
Required:
• TS/SCI CI Poly Clearance with current NGA eligibility and SBU/SecNet/COE accounts
• Must be willing to work in SCIF daily or as needed
• 5+ years of professional machine learning engineering experience with a focus on deep learning
• 4+ years of advanced Python development for ML workloads
• 3+ years of experience with computer vision or multimodal models
• 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)
• 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
• 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
• Strong proficiency with PyTorch and the HuggingFace ecosystem (Transformers, PEFT, Datasets, Accelerate)
• Experience with distributed training frameworks (DeepSpeed, FSDP, or Megatron)
• Understanding of vision transformer architectures (ViT, CLIP, LLaVA-family models, or similar)
• Experience processing and augmenting image datasets at scale
• Strong software engineering fundamentals (version control, CI/CD for ML workflows, testing)
Preferred:
• 2+ years of experience with geospatial or remote sensing imagery
• 2+ years of experience with Authority to Operate (ATO) processes in government environments
• 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, ES/EKS)
• 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
Company:
Welcome to NewGen Technologies, Inc. Founded in 1997, the company is headquartered in Fulton, USA, with a team of 51-200 employees. The company is currently Growth Stage.

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