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Contract Data Annotation Jobs in Lexington, KY (NOW HIRING)

Contract Data Annotation information

What is the difference between Contract Data Annotation vs Data Labeler?

AspectContract Data AnnotationData Labeler
CredentialsBasic computer skills, attention to detailBasic computer skills, attention to detail
Work EnvironmentRemote or on-site, project-basedRemote or on-site, task-based
Industry UsageAI/ML training, tech companiesAI/ML training, tech companies
Job FocusAnnotating data for machine learning modelsLabeling data to improve AI algorithms

Contract Data Annotation involves completing specific annotation projects for AI training, often on a contractual basis. Data Labelers focus on labeling data to enhance machine learning models, typically performing similar tasks. Both roles require attention to detail and are used in AI/ML industries, but Contract Data Annotation emphasizes project-based work with defined deliverables.

What is a contract data annotation?

A contract data annotation job involves labeling or tagging data—such as images, text, audio, or video—according to specific guidelines, usually on a temporary or project-based contract. These annotations help train machine learning models by providing accurate, human-labeled examples for algorithms to learn from. Contract workers are typically hired for a set period or project and may work remotely or on-site, depending on the employer. The work requires attention to detail, adherence to quality standards, and sometimes familiarity with specialized annotation tools.

What are the key skills and qualifications needed to thrive as a contract data annotation specialist?

To thrive as a Contract Data Annotation Specialist, you need a keen eye for detail, strong analytical skills, and familiarity with data labeling standards, often supported by experience in data management or related fields. Proficiency with annotation platforms (such as Labelbox, Prodigy, or CVAT) and basic knowledge of data formats like JSON or XML are commonly required. Excellent communication, time management, and the ability to work independently help individuals excel in this often remote and deadline-driven role. These skills ensure high-quality, accurate data annotations that are vital for training reliable machine learning models.

What are some common challenges faced by contract data annotation professionals, and how can they be effectively managed?

Contract data annotation professionals often encounter challenges such as maintaining consistency in labeling, managing tight project deadlines, and ensuring data privacy. These challenges can be effectively managed by following detailed annotation guidelines, utilizing collaborative tools for team communication, and participating in regular quality assurance checks. Staying organized and proactive about seeking clarification from project leads also helps ensure high-quality, accurate results and a smooth workflow.
What job categories do people searching Contract Data Annotation jobs in Lexington, KY look for? The top searched job categories for Contract Data Annotation jobs in Lexington, KY are:
What cities near Lexington, KY are hiring for Contract Data Annotation jobs? Cities near Lexington, KY with the most Contract Data Annotation job openings:

Manufacturing Innovation Advanced Technology Engineer

Calance US

Georgetown, KY • On-site

Contractor

Medical, Dental, Vision, Life

Posted 4 days ago


Job description

We are hiring Manufacturing Innovation Advanced Technology Engineer for a Contract position in Georgetown, KY
CALL US NOW for immediate consideration! Click Apply on Web or Apply Now to view our recruiter s contact info and reach out today, we d love to speak with you!
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** We will NOT accept 3rd Party (C2C) Contractors **
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JOB DETAILS:
Position:Manufacturing Innovation Advanced Technology Engineer
JOB REF#:44282 - 1475216
Duration:12+ Months (On-Going Contract)
Location:ONSITE - Georgetown, KY 40324
Pay Rate:OPEN/Market Rate (W2 Only)
** Must be LOCAL or willing to RELOCATE at your own expense**
** This is role is 100% ONSITE, no remote work offered**
The Manufacturing Project Innovation Center (Manufacturing Innovation) Advanced Technology Department is looking for a passionate and highly motivated, Advanced Technology Engineer
Model Development & Training Speed
Design and implement computer vision models for defect detection, segmentation, and classification.
Accelerate training cycles using synthetic data, active learning, and domain randomization to cover rare defects and specification variance.
Production Deployment
Package models and services using Docker and manage deployments through Kubernetes or equivalent orchestration tools.
Implement version control, rollback strategies, and observability for latency, drift, and false-positive/false-negative metrics.
Edge Optimization
Optimize inference for edge and embedded hardware (e.g., NVIDIA Jetson, Intel accelerators) to meet strict real-time latency requirements for moving-line inspection.
Ensure consistent performance under varying lighting, optics, and surface conditions.
Integration with Manufacturing Systems
Integrate vision systems with PLCs, encoders, triggers, and industrial networks using OPC-UA, MQTT, and REST protocols.
Align deployments with Toyota s ICS+, GALC, and TVIP architecture standards for plant-level connectivity and reliability.
Data Strategy & Quality Control
Lead data collection campaigns, manage annotation workflows, and establish quality gates for model validation.
Utilize synthetic data pipelines and augmentation techniques to improve model robustness and reduce training time.
Reliability & Sustainment
Ensure uptime and availability targets are met through proactive monitoring, calibration (MSA), and backup/restore processes.
Implement drift detection, audit false-out risks, and perform root cause analysis for inspection failures.
DAILY TASKS:
Develop and deploy production-grade machine learning models for industrial vision inspection systems across manufacturing lines.
Accelerating model development and training using advanced techniques such as synthetic data generation, ensuring high accuracy and generalization, and delivering containerized software optimized for edge hardware
Development of new technologies for PE and Manufacturing competitiveness improvement
Lead and manage projects from concept to launch for new technology first introduction to manufacturing including creating schedules, establishing punch lists, and meeting established due dates and milestones.
Search for innovative solutions, test them in a manufacturing setting, and develop business case justification to gain approval to purchase if trials prove successful.
Close collaboration between both internal and external groups, including North American Manufacturing Centers and IT to ensure quality and to integrate robust AI solutions into high-volume manufacturing environments.
REQUIRED SKILLS/EXPERIENCE:
Able to travel to all North American Manufacturing Centers (NAMC s), including Canada, Japan and Mexico
5 years of experience in Industrial Machine Vision & Edge AI development/deployments.
Experienced with machine learning and vision systems using PLC.
Proficiency in Python and C++ with strong knowledge of ML frameworks (PyTorch, TensorFlow).
Experience with project management including writing detailed scope of work, creating schedules, managing vendors/contractors, and providing regular status updates
Hands-on experience with containerization (Docker) and orchestration (Kubernetes).
Familiarity with ONNX Runtime, TensorRT, and optimization for embedded hardware.
Experience integrating vision systems with PLCs and industrial protocols (OPC-UA, MQTT).
Experience managing the full model lifecycle: data collection, labeling, validation, rollout, monitoring, and retraining
Experience in areas such as object detection, classification, segmentation and familiarity with mainstream object detection and semantic/instance segmentation models.
Familiarity with industrial cameras, lighting, and optics, including trigger-based image capture
Experience balancing inspection accuracy with false positives vs flow-out risk in quality
EDUCATION: Bachelor s degree in Electrical Engineering, Mechanical Engineering, Computer Science, Information Technology or related field.
Desired Skills/Nice To Have's:
Master s Degree in Engineering or Advanced Degree in related fields
Academic research experience in new technology
Project management work involving internal and external parties
Experience deploying equipment including establishing RJ, PFMEA, and quality control plan
Experience deploying automotive production equipment
Experience in Robotics to include operation, teaching, maintenance, and safety
Expertise in synthetic data generation techniques (GANs, VAEs, NeRFs, Blender) and domain randomization for model generalization.
Experience with high-speed inline inspection systems and vision-based process control.
Knowledge of IIoT data pipelines and messaging standards.
Strong understanding of calibration, measurement system analysis (MSA), and quality-critical inspection requirements.
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Calance Consultant Benefits Offerings:
- EPO/PPO Medical Plans
- HMO/PPO Dental programs
- Vision - VSP (Vision Plan Summary)
- 401K Retirement vesting program (VOYA)
- Paid Bi-Weekly/Direct Deposit
- Flex Spending Plan
- Voluntary Life, AD&D, STD or LTD plans
Estimated Pay Range: