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Data Annotation Engineer Jobs in Atlanta, GA (NOW HIRING)

Czarnowski Collective

CAD MECHANICAL DESIGNER

Austell, GA · On-site

$65 - $95/hr

You'll develop and manage engineering data in accordance with Czarnowski CAD standards while ... Microsoft Office, scheduling software, Adobe Acrobat review and annotation What we offer: * Medical ...

New

Czarnowski

CAD MECHANICAL DESIGNER

Austell, GA · On-site

You'll develop and manage engineering data in accordance with Czarnowski CAD standards while ... Microsoft Office, scheduling software, Adobe Acrobat review and annotation What we offer: * Medical ...

Merrick & Company

GIS Technician Intern

Chamblee, GA

$16.50 - $21.25/hr

Data management * GIS * Cartographic design * Must meet expectations for attendance and punctuality ... Labeling and annotation * Projection and scale * Basic cartographic methodologies * Familiarity ...

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All JobsData Annotation Engineer JobsData Annotation Engineer Jobs in Atlanta, GA

Data Annotation Engineer information

See Atlanta, GA salary details

$49.5K

$141.8K

$189.4K

How much do data annotation engineer jobs pay per year?

As of Sep 4, 2026, the average yearly pay for data annotation engineer in Atlanta, GA is $141,807.00, according to ZipRecruiter salary data. Most workers in this role earn between $80,800.00 and $188,500.00 per year, depending on experience, location, and employer.

What is a data annotation engineer?

A Data Annotation Engineer is responsible for labeling and annotating data—such as text, images, audio, or video—to train machine learning models. They ensure that data is accurately categorized and structured to improve model performance. This role often involves using specialized annotation tools, following detailed guidelines, and working closely with data scientists and AI teams. Data Annotation Engineers play a crucial role in the development of AI applications by providing high-quality labeled datasets for supervised learning.

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

To thrive as a Data Annotation Engineer, you need a strong background in data analysis, attention to detail, and familiarity with annotation processes, often supported by a degree in computer science or a related field. Proficiency with annotation tools like Labelbox, CVAT, or VIA, and understanding of data formats used in machine learning, is commonly required. Excellent communication, collaboration, and organizational skills help you effectively manage projects and cooperate with cross-functional teams. These abilities are crucial for delivering high-quality labeled data, which directly impacts the performance of AI and machine learning models.

What are the main challenges faced by data annotation engineers in their daily work?

One of the main challenges Data Annotation Engineers face is ensuring consistent accuracy and quality in labeling large and often complex datasets. Attention to detail is critical, as even small errors can significantly affect machine learning model performance. Additionally, engineers must frequently adapt to evolving annotation guidelines and emerging data types, which requires ongoing learning and flexibility. Collaboration with data scientists and project managers is common to clarify requirements and resolve ambiguities, making strong communication skills essential for success.

What is the salary of data annotation engineer?

The salary of a data annotation engineer typically ranges from $40,000 to $80,000 annually, depending on experience, location, and the complexity of annotation tasks. Entry-level positions may start lower, while experienced professionals with specialized skills in tools like Labelbox or CVAT can earn higher salaries.

What are popular job titles related to Data Annotation Engineer jobs in Atlanta, GA?

For Data Annotation Engineer jobs in Atlanta, GA, the most frequently searched job titles are:

What job categories do people searching Data Annotation Engineer jobs in Atlanta, GA look for?

The top searched job categories for Data Annotation Engineer jobs in Atlanta, GA are:

What cities near Atlanta, GA are hiring for Data Annotation Engineer jobs?

Cities near Atlanta, GA with the most Data Annotation Engineer job openings:

Data Annotation Engineer jobs near you
Infographic showing various Data Annotation Engineer job openings in Atlanta, GA as of August 2026, with employment types broken down into 1% As Needed, 83% Full Time, 12% Part Time, and 4% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $141,807 per year, or $68.2 per hour.

Bioinformatics Specialist

BeVera Solutions LLC

Atlanta, GA • On-site

Full-time

Posted 7 days ago

Job description

Description

About BeVera Solutions, LLC 

BeVera Solutions, LLC is a rapidly growing public health and professional services company that provides innovative solutions to federal and state agencies. Our team supports mission-critical programs through expertise in program management, communications, acquisition, data analytics, and public health initiatives. BeVera's CEO champions a people-first culture where every employee is valued. The company supports this commitment by offering competitive compensation and meaningful, impactful work assignments.  


Recognized as one of Atlanta's Best Places to Work (2024 & 2025 & 2026) by the Atlanta Business Chronicle, BeVera fosters a culture of integrity, excellence, and collaboration.


NOTE: Position Contingent upon award of contract.  This role is part of a pre-award candidate search for an upcoming federal government contract.  Employment is contingent upon BeVera Solutions receiving the contract award, final Government approval, funding, and any applicable client or contract requirements.  

Job Description Essential Duties

BeVera Solutions is seeking a highly experienced Bioinformatician - Scientific Computing & Genomics to perform genomic data analysis and develop, execute, maintain, and troubleshoot reproducible bioinformatics workflows supporting CDC's Office of Advanced Molecular Detection (OAMD).

The position supports next-generation sequencing, microbial genomics, scientific scripting, workflow development, HPC and cloud computing, statistical analysis, and technical consultation for public-health laboratory and pathogen-analysis activities.


Bioinformatics & Genomic Analysis

  • Perform bioinformatics analysis of next-generation and other high-throughput sequencing data. 
  • Support genome sequencing, assembly, annotation, microbial genomics, metagenomics, transcriptomics, phylogenetics, and related analyses. 
  • Conduct statistical analyses and scientific data-quality reviews. 
  • Process and analyze complex genomic and other biological datasets. 

Workflow Development & Scientific Programming

  • Develop, execute, modify, test, document, and maintain reproducible bioinformatics workflows. 
  • Develop and support workflows using Nextflow and related workflow-management technologies. 
  • Create scientific scripts and analytical tools using Python, R, Perl, Java, BioPerl, or similar languages. 
  • Optimize pipelines for computational efficiency, storage utilization, scalability, and reproducibility. 

HPC, Cloud & Software Environment Support

  • Adapt bioinformatics workflows and algorithms to HPC and cloud-computing environments. 
  • Support implementation, configuration, testing, and validation of open-source, commercial, and custom bioinformatics software. 
  • Assist with containerized bioinformatics applications and scientific-computing environments. 
  • Maintain and update reference datasets, databases, software environments, and analytical resources. 
  • Troubleshoot workflow failures, software dependencies, data-format compatibility issues, analytical errors, and computational-resource problems. 

Quality Assurance, Validation & Documentation

  • Participate in software testing, quality-control, validation, and user-acceptance activities. 
  • Document analytical methods, workflows, software configurations, results, and technical procedures. 
  • Contribute to technical reports, scientific presentations, manuscripts, methods documentation, and other program products as needed. 

Scientific Consultation & User Support

  • Provide bioinformatics technical consultation and user support appropriate to level of experience. 
  • Assist scientists and technical users in understanding bioinformatics tools, analyses, workflows, and results. 

Collaboration, Training & Leadership

  • Collaborate with bioinformaticians, scientists, system administrators, DevOps personnel, infrastructure teams, data-management personnel, and other technical staff. 
  • Participate in technical training, knowledge-sharing, and continuous professional development. 
  • Senior-level incumbents may mentor less-experienced bioinformatics personnel and lead complex analytical assignments.

Requirements

Required Qualifications

  • Demonstrated education, training, or professional experience related to bioinformatics, computational biology, genomics, biological sciences, computer science, data science, or a closely related field.
  • Knowledge of bioinformatics methods and genomic or sequencing-data analysis.
  • Experience or demonstrated proficiency with scientific scripting or statistical programming.
  • Ability to work with large and complex scientific datasets.
  • Ability to document analytical methods and technical procedures.
  • Strong analytical, problem-solving, and communication skills.
  • Ability to work collaboratively within multidisciplinary scientific and technical teams.

Preferred Qualifications

Experience supporting public-health, infectious-disease, laboratory-science, HHS, CDC, or other federal scientific programs is also preferred.

Programming & Scientific Computing

  • Python      
  • R 
  • Perl 
  • Java/BioPerl
  • Linux 
  • High-performance computing (HPC) 
  • Cloud-computing environments 

Bioinformatics Workflows & Development

  • Nextflow      
  • nf-core/ph-core or similar workflow standards 
  • Bioinformatics workflow optimization 
  • Containers/Singularity or similar technologies 
  • Scientific software testing and validation 

Genomics & Sequence Analysis

  • Next-generation sequencing (NGS) and high-throughput sequencing 
  • Genome assembly 
  • Functional annotation 
  • Microbial genomics 
  • Metagenomics      
  • Phylogenetic analysis 

Data Analysis & Public Health

  • Statistical analysis 
  • Epidemiologic or public-health data

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