Role: M/L Data Engineer - Python & Computer Vision
Location: Mclean, VA(Local Only)
Exp: 10+ years
$80/hour on W2
Contract
Position Overview:
We are seeking a hands-on Data Scientist with strong Python and Computer Vision skills to design, build, test, and operationalize capabilities that convert image-based content and model outputs into usable, reviewable, and analytics-ready data products. This role requires strong software engineering fundamentals, computer vision coding experience, data engineering skills, and the ability to partner across product, modeling, engineering, research, and business teams. The Data Scientist will contribute to capabilities for image extraction, metadata generation, model-output validation, quality review enablement, and downstream structured data integration. The role is expected to balance Python development, testing, analytical troubleshooting, and delivery execution to help users review, validate, and act on computer vision outputs.
Key Responsibilities:
Computer Vision Development & Model Output Engineering
Develop, enhance, and maintain code that supports computer vision model output processing, image extraction, metadata generation, and validation workflows
Work with image-based model outputs, bounding boxes, labels, confidence scores, extracted attributes, and structured metadata to support downstream review and analysis
Build reusable utilities for parsing, transforming, validating, and comparing computer vision outputs across model versions and production-style runs
Apply strong Python coding practices to automate testing, issue detection, data preparation, and model-output quality checks
Product & QC Workflow Enablement
Support product capabilities that allow users to review, validate, correct, and quality check model-generated outputs
Translate computer vision models output into user-facing review patterns, QC screens, exception workflows, and validation experiences
Partner with UI developers, product owners, and business users to define practical capabilities for model-output inspection and operational review
Test Data, Validation & Quality Engineering
Create and manage representative test datasets for image extraction, metadata validation, regression testing, and model performance review
Perform structured testing of model runs across historical and current datasets to identify extraction gaps, metadata issues, formatting errors, and quality concerns
Validate extracted images, image classifications, and metadata against original PDFs, appraisal reports, and other authoritative source documents to confirm completeness, accuracy, and traceability
Document defects with clear evidence, expected results, actual results.
Retest remediated issues and contribute to repeatable quality gates for model-output readiness
Data Integration, JSON Engineering & Analytics Readiness Develop scripts and data pipelines that convert model outputs into structured and semi-structured formats suitable for research, analytics, and downstream consumption
Support loading and validation of model outputs as JSON Variant or similar semi-structured data formats
Ensure extracted image attributes, metadata, and model-output payloads are traceable, consistent, and accessible for analysis
Cross-Functional Delivery & Technical Problem Solving
Collaborate across product management, model development, UI engineering, data engineering, research, business, and delivery teams to operationalize computer vision capabilities within data-driven products
Investigate technical issues across image inputs, model outputs, metadata payloads, data loads, and user-facing QC workflows
Communicate progress, risks, blockers, and technical findings clearly to engineering partners and business stakeholders
Required Qualifications
Computer Vision Coding & Software Engineering Hands-on experience coding computer vision or image-processing solutions using Python and common libraries such as OpenCV, Pillow, PyTorch, TensorFlow, or similar frameworks
Strong ability to process image files, extracted labels, model predictions, confidence scores, annotations, bounding boxes, and metadata payloads
Experience writing modular, maintainable code for automation, validation, transformation, testing, and troubleshooting

M/L Data Engineer - Python & Computer Vision @ Mclean, VA(Local Only)

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