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Data Annotation Tech Remote Jobs in Colorado (NOW HIRING)

KORE1 Technologies

Head of Data Platform

Denver, CO · Remote

... remote. Why This Role Exists We operate a large-scale, multi-tenant SaaS platform supporting ... collaborative technology organization focused on building scalable platforms that improve ...

ProEdge Dental Water Labs

Head of Technology

Centennial, CO · On-site +1

$140K - $170K/yr

You've mapped the landscape across systems, data, integrations, and where the real friction lives ... This is a hybrid in-office/remote role with a core schedule of 8:00 AM - 5:00 PM, Monday through ...

SAIC

IT Systems Engineer

Colorado Springs, CO · On-site +1

$120K - $160K/yr

TS/SCI Potential for Remote Work: ORA_ON_SITE Description SAIC is seeking a Mid-Level IT Systems ... Conduct system performance management, capacity planning, and funnel potential data-driven upgrades ...

Prologis

Program Director, Data & Analytics

Denver, CO · On-site +1

... remote teams * Strong change management mindset and comfort operating in evolving environments ... Demonstrate willingness and capability toleverageemerging technology, automation, and AI tools to ...

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Data Annotation Tech Remote information

What is the difference between Data Annotation Tech Remote vs Data Labeling Specialist?

AspectData Annotation Tech RemoteData Labeling Specialist
CredentialsBasic technical skills, sometimes certifications in data annotation toolsSimilar credentials, often with experience in labeling software
Work EnvironmentRemote, often freelance or contract-basedRemote or on-site, depending on employer
Industry UsageUsed across AI, machine learning, and data science companiesCommon in AI, autonomous vehicles, and tech firms

Both roles involve labeling data for machine learning models, with similar credentials and remote work options. The main difference lies in job titles used by employers, but their responsibilities and industry applications overlap significantly.

What are Data Annotation Tech Remote jobs?

Data Annotation Tech Remote jobs involve working from home or another remote location to label, tag, or classify data such as text, images, audio, or video. This work is essential for training and improving artificial intelligence and machine learning models. Data annotators use specialized software tools to accurately identify and categorize data according to specific guidelines provided by employers. These roles require attention to detail, consistency, and sometimes subject-matter expertise, depending on the project. Remote data annotation jobs are popular because they often offer flexible schedules and the ability to work from anywhere.

What are some common challenges faced by remote Data Annotation Technicians, and how can they be addressed?

Remote Data Annotation Technicians often encounter challenges such as maintaining consistent annotation quality, managing repetitive tasks, and ensuring clear communication with team leads or project managers. To address these, it's helpful to establish a structured daily routine, use collaboration tools to stay connected with the team, and regularly review project guidelines to ensure accuracy. Many organizations also provide feedback loops and quality assurance checks, so being proactive in seeking feedback can help improve performance and job satisfaction.

What are the key skills and qualifications needed to thrive as a Data Annotation Tech (Remote), and why are they important?

To excel as a Data Annotation Tech (Remote), you need attention to detail, basic computer literacy, and familiarity with data labeling practices, often supported by a high school diploma or equivalent. Proficiency with annotation tools such as Labelbox, Supervisely, or proprietary platforms is typically required, and training in data privacy or quality assurance may be beneficial. Strong communication, time management, and the ability to focus independently are standout soft skills for this remote role. These competencies are crucial to ensure accurate, high-quality data labeling that directly impacts the effectiveness of AI and machine learning models.
What are popular job titles related to Data Annotation Tech Remote jobs in Colorado? For Data Annotation Tech Remote jobs in Colorado, the most frequently searched job titles are:
What job categories do people searching Data Annotation Tech Remote jobs in Colorado look for? The top searched job categories for Data Annotation Tech Remote jobs in Colorado are:
What cities in Colorado are hiring for Data Annotation Tech Remote jobs? Cities in Colorado with the most Data Annotation Tech Remote job openings:
Data Annotation Tech Remote jobs near you
Head of Data Platform

Head of Data Platform

KORE1 Technologies

Denver, CO • Remote

Contractor

Medical, Dental, Vision, Life, Retirement, PTO

Posted 28 days ago

Job description


KORE1, a nationwide provider of staffing and recruiting solutions, has an immediate opening for a Head of Data Platform that is fully remote. 

Why This Role Exists
We operate a large-scale, multi-tenant SaaS platform supporting thousands of enterprise customers nationwide. Our data ecosystem - spanning relational databases, NoSQL systems, streaming events, and cloud-based data lakes - powers complex transactional workflows, integrations, analytics, and operational decision-making at scale.

As the platform evolves, we are building intelligent, closed-loop optimization systems capable of observing operational signals, predicting outcomes, automating decisions, and continuously learning from results. These systems rely on scalable feature engineering, real-time data pipelines, model infrastructure, telemetry, and strong governance controls.

This role will own the foundational data architecture that enables those capabilities. You will lead the design of the data platform, feature infrastructure, governance framework, and real-time data systems that transform a transactional SaaS platform into an intelligent decision engine.
This is a highly hands-on leadership role focused on modern data architecture, AI/ML infrastructure, streaming systems, governance, and scalable platform engineering.
Scope & Scale
  • Large-scale multi-tenant SaaS environment supporting thousands of enterprise customers
  • High-volume transactional and operational data workloads
  • Complex third-party integrations spanning multiple data formats and protocols
  • Real-time streaming systems and event-driven architectures
  • Multiple optimization and intelligent automation initiatives requiring scalable feature engineering and telemetry systems
What You Will OwnData Platform Architecture
  • Design and own the end-to-end data platform architecture including raw ingestion, canonical entity modeling, analytics layers, feature infrastructure, and telemetry systems.
  • Build scalable frameworks for feature engineering, data quality, lineage, governance, and operational reliability.
  • Define patterns for tenant isolation, auditability, retention policies, and secure data access at scale.
Feature Store & AI Data Infrastructure
  • Lead the design and operation of online and offline feature infrastructure supporting real-time scoring and model training workflows.
  • Establish standards for feature ownership, freshness SLAs, training/inference parity, metadata governance, and lifecycle management.
  • Build scalable pipelines supporting ML models, intelligent automation workflows, and AI-enabled platform capabilities.
Streaming & Event-Driven Systems
  • Design and operate real-time streaming pipelines, event-driven data propagation, and change-data-capture systems.
  • Support low-latency feature materialization and telemetry processing across distributed services.
  • Ensure scalability, observability, and reliability across streaming infrastructure.
Data Governance & Quality
  • Establish enterprise-grade governance frameworks covering PII handling, tenant isolation, retention policies, audit logging, and cost attribution.
  • Implement automated monitoring for schema drift, stale pipelines, null spikes, feature skew, and data inconsistencies.
  • Own data quality standards and operational accountability across the platform.
Platform Modernization & Migration Strategy
  • Lead data migration and modernization initiatives across relational and NoSQL systems.
  • Define scalable migration patterns including dual-write validation, reconciliation strategies, and zero-downtime cutovers.
  • Partner with Engineering, Infrastructure, Product, and AI teams to align platform evolution with business goals.
Technical Leadership
  • Mentor engineers and data practitioners across multiple teams.
  • Drive architecture reviews, data modeling standards, and platform engineering best practices.
  • Establish scalable operating mechanisms and technical governance processes.
Technical EnvironmentData Platforms & Storage
  • Relational and NoSQL systems including Aurora/MySQL/PostgreSQL, DynamoDB, S3 data lakes, and distributed storage architectures
  • Modern lakehouse and analytical storage patterns
Streaming & Event Systems
  • Event-driven architectures, streaming pipelines, CDC frameworks, and real-time feature propagation systems
AI & ML Infrastructure
  • Feature stores, model training pipelines, model lifecycle infrastructure, and AI-enabled workflow systems
  • Production AI/ML deployment and observability frameworks
Data Engineering & Analytics
  • ETL/ELT orchestration platforms
  • Distributed analytics environments and BI tooling
  • Metadata cataloging, governance, and observability systems
Infrastructure & DevOps
  • AWS cloud infrastructure, infrastructure-as-code, CI/CD, monitoring, and operational tooling
Hands-On Expectations
This is not a purely strategic leadership role. The expectation is a strong balance of:
  • hands-on engineering and SQL/data work
  • architecture and systems design
  • technical mentorship and cross-functional leadership
You should be comfortable operating both as a high-level architect and as a deeply technical contributor on critical systems and pipelines.
First 12 MonthsMonths 1-3
  • Evaluate the existing data landscape, integrations, pipelines, and governance gaps
  • Define canonical entity models and future-state data architecture standards
  • Publish initial architecture recommendations and modernization priorities
Months 4-6
  • Establish foundational feature infrastructure and governance frameworks
  • Deliver initial modernization and migration initiatives
  • Implement automated monitoring and data quality controls
Months 7-9
  • Support production deployment of optimization and intelligent automation workflows
  • Operationalize feature lifecycle management, telemetry systems, and model infrastructure
  • Expand streaming and event-driven capabilities across the platform
Months 10-12
  • Deliver additional production-scale optimization and AI-enabled data capabilities
  • Mature governance, observability, and platform reliability standards
  • Define long-term roadmap for data platform scalability and intelligent systems evolution
RequirementsRequired Qualifications
  • 7+ years of experience in data engineering, platform engineering, or data architecture roles
  • Experience operating at a senior architect, principal, or platform leadership level
  • Deep expertise in both relational and NoSQL data modeling and distributed data systems
  • Strong experience building scalable feature infrastructure and real-time data platforms
  • Hands-on experience with cloud-native AWS data and analytics services
  • Experience supporting AI/ML workflows, feature engineering, or production AI systems
  • Strong understanding of event-driven architectures, CDC, and streaming data systems
  • Experience with large-scale multi-tenant platform architectures and governance challenges
  • Strong data governance instincts around security, auditability, PII handling, and operational accountability
  • Ability to balance architecture leadership with hands-on implementation work
Strongly Preferred
  • Experience supporting AI/ML lifecycle infrastructure including feature stores, model registries, monitoring, and production deployment workflows
  • Experience with LLM-related infrastructure, embeddings pipelines, retrieval systems, or intelligent automation workflows
  • Experience building closed-loop analytics or optimization systems with telemetry and outcome tracking
  • Strong experience with data quality monitoring and anomaly detection at scale
  • Familiarity with lakehouse architectures, open table formats, and large-scale analytical systems
Nice to Have
  • Experience in SaaS, fintech, automotive, marketplace, or transaction-heavy industries
  • Familiarity with complex third-party integrations and heterogeneous data sources
  • Experience with vector databases or semantic retrieval systems
  • Exposure to optimization, recommendation, scheduling, or operational intelligence systems
Benefits & Culture
We are a fast-paced and collaborative technology organization focused on building scalable platforms that improve operational efficiency, intelligent automation, and customer outcomes.
We offer:
  • Comprehensive medical, dental, and vision coverage
  • Employer-sponsored disability and life insurance
  • 401(k) with company match
  • Generous paid time off and company holidays
  • High-impact ownership over foundational AI and data platform initiatives
  • Opportunity to shape next-generation intelligent systems at scale




Compensation depends on experience but is typically 160k-195k

ABOUT KORE1
Specializing in professional and technical recruiting, KORE1 is committed to supporting top IT, Engineering, Creative, Scientific, Accounting and Finance professionals in their career paths. We build deep relationships with leading companies, connecting them to exceptional talent every day. With extensive industry expertise and unmatched opportunities, our goal is to provide a unique experience for our contractors and consultants as they prepare for their next role. We are passionate about matching the right people with the right companies.

Kore1 provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, sex, national origin, age, disability or genetics. In addition to federal law requirements, Kore1 complies with applicable state and local laws governing nondiscrimination in employment in every location in which the company has facilities. This policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation and training. Kore1 expressly prohibits any form of workplace harassment based on race, color, religion, gender, sexual orientation, gender identity or expression, national origin, age, genetic information, disability, or veteran status. Improper interference with the ability of Kore1's employees to perform their job duties may result in discipline up to and including discharge.
Education:Employment Type: CONTRACTOR

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