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Ai Data Labeling Remote Jobs in Baltimore, MD (NOW HIRING)

Under Armour

Sr. Data Analytics Engineer

Baltimore, MD · On-site +1

$125K - $165K/yr

Partnering with Analytics, Automation & AI, and Governance teams, you will deliver trusted data ... Location: Remote (East Coast strongly preferred to optimize collaboration with HQ and cross ...

Global Alliant Inc

AI Engineer

Baltimore, MD · Remote

Remote Job Duration: Fulltime Client: Federal Criteria- Need ship because of federal regulations ... Ability to obtain Public Trust Clearance * 5+ years of experience in AI/ML, Data Science, Data ...

Global Alliant Inc

AI Engineer

Baltimore, MD · Remote

Remote Job Duration: Fulltime Client: Federal Criteria- Need ship because of federal regulations ... Ability to obtain Public Trust Clearance * 5+ years of experience in AI/ML, Data Science, Data ...

Booz Allen Hamilton, Inc.

Data Scientist

Edgewood, MD · On-site +1

$77K - $176K/yr

Remote Work: No Job Number: R0238506 Location: Edgewood,MD,US Share job via: Share Data Scientist ... Experience working with Machine Learning, Artificial Intelligence (AI), or Natural Language ...

Moore

Lead Agentic AI Engineer - Remote US

Lanham, MD · Remote

$165K - $175K/yr

Moore is the largest nonprofit marketing, data, and fundraising company in North America - 5,000 ... AI/ML or agentic systems * Location: Remote (US). Occasional travel for team offsites and customer ...

T Rowe Price

Lead Data Engineer

Baltimore, MD · On-site +1

$113K - $136K/yr

Rowe Price's data and AI capabilities. * Troubleshoot and optimize data solutions and platform ... Work Flexibility This role is eligible for full time remote work.

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Ai Data Labeling Remote information

See Baltimore, MD salary details

$23.1K

$98.5K

$227.7K

How much do ai data labeling remote jobs pay per year?

As of Aug 26, 2026, the average yearly pay for ai data labeling remote in Baltimore, MD is $98,537.00, according to ZipRecruiter salary data. Most workers in this role earn between $37,697.00 and $146,264.00 per year, depending on experience, location, and employer.

What is an AI data labeling remote?

An AI Data Labeling Remote job involves annotating data, such as images, text, audio, or videos, to help train machine learning models. Tasks may include drawing bounding boxes, categorizing content, or transcribing text with accuracy. This role is typically performed online, allowing individuals to work from home with flexible hours. Strong attention to detail and familiarity with labeling tools are essential for success in this position.

What are the key skills and qualifications needed to thrive in the AI data labeling remote position, and why are they important?

To thrive as an AI Data Labeling Remote professional, you need keen attention to detail, strong organizational skills, and familiarity with data annotation concepts, typically supported by a high school diploma or relevant experience. Proficiency with common labeling tools like Labelbox, Supervisely, or proprietary platforms, and a basic understanding of data privacy and security protocols, are often required. Consistency, reliability, time management, and clear communication are crucial soft skills that set candidates apart. These abilities ensure high-quality, accurate labeling of datasets, which is critical for training effective and unbiased AI models.

What are some typical challenges faced by AI data labeling remote professionals, and how can they be overcome?

Remote AI data labeling professionals often encounter challenges such as maintaining attention to detail over repetitive tasks and ensuring consistent quality across large datasets. To overcome these challenges, it's helpful to take regular breaks, stay organized with task management tools, and actively communicate with your team leaders about any uncertainties or edge cases in the data. Many teams provide detailed guidelines and ongoing feedback to support accuracy and minimize errors. Adhering to best practices and engaging in regular check-ins with supervisors can help maintain motivation, ensure consistent performance, and contribute positively to team goals.

What are the most commonly searched types of Ai Data Labeling jobs in Baltimore, MD?

The most popular types of Ai Data Labeling jobs in Baltimore, MD are:

What are popular job titles related to Ai Data Labeling Remote jobs in Baltimore, MD?

For Ai Data Labeling Remote jobs in Baltimore, MD, the most frequently searched job titles are:

What job categories do people searching Ai Data Labeling Remote jobs in Baltimore, MD look for?

The top searched job categories for Ai Data Labeling Remote jobs in Baltimore, MD are:

What cities near Baltimore, MD are hiring for Ai Data Labeling Remote jobs?

Cities near Baltimore, MD with the most Ai Data Labeling Remote job openings:

Ai Data Labeling Remote jobs near you
Infographic showing various Ai Data Labeling Remote job openings in Baltimore, MD as of August 2026, with employment types broken down into 2% Internship, 67% Full Time, 17% Part Time, and 14% Contract. Highlights an 100% Remote job distribution, with an average salary of $98,537 per year, or $47.4 per hour.

Data Engineer - ML/AI Data Platform (Remote)

FEI Systems

Columbia, MD • On-site, Remote

$111K - $133K/yr

Full-time

Re-posted 17 days ago

Job description

At FEI Systems, we create innovative technology solutions to improve the delivery of health and human services because we know when cumbersome administrative processes stand in the way, those who need it most are often left without access to proper care and support. From comprehensive case management software to disaster recovery services and content management information systems used in delivering foreign aid, our solutions are improving the lives of millions of people. We're looking for a data engineer who shares our commitment to leveraging technology to make a real impact in the world - a professional who knows, beyond all else, that the quality of our products and services is only as good as the company we keep.
All candidates will be required to complete at least one in-person interview as part of our hiring process.
Role Overview
We are seeking a Data Engineer to support Machine Learning and AI initiatives. Working closely with the Solution Architect, Data Architect, DevOps, and Application Engineering teams, this role is responsible for ensuring that data within our cloud-based platform is high quality, well-governed, feature-ready, and production-grade to support model training, deployment, and ongoing operations.
The ideal candidate has 5+ years of cloud data engineering experience with strong proficiency in Snowflake, Python, and SQL, and solid familiarity with AWS-native data services.
Candidates are not expected to arrive with expertise across every area listed. We are looking for demonstrated strength in the core data engineering and Snowflake skills, combined with the initiative and aptitude to grow into the broader scope of the role.
Day-One Priorities & Scope
Immediate focus is Snowflake-based data engineering, pipeline development, and data quality. Feature engineering, model training support, and MLOps contributions are growth areas that will ramp over time as you become embedded with the team.
Key Responsibilities
Data Pipeline Engineering
  • Design, build, and maintain scalable data pipelines supporting ML/AI workloads.
  • Engineer pipeline patterns including full loads, incremental loads, change-based loads, and slowly changing dimensions.
  • Ensure pipelines are reliable, performant, secure, and maintainable, troubleshoot and monitor pipelines within an AWS ecosystem.

Snowflake & Cloud Data Engineering
  • Perform data transformations in Snowflake using SQL and native Snowflake features.
  • Design and optimize schemas, tables, views, and materialized views for ML/AI consumption.
  • Support AWS-native data lake patterns using S3, Glue, Athena, Apache Iceberg, and S3 Tables.

Feature Engineering & Data Preparation
  • Perform data cleansing, normalization, and enrichment to support ML model development.
  • Design and implement feature engineering pipelines including aggregation and transformation.
  • Ensure consistency, reuse, and versioning of features across models and use cases.
  • Support feature store patterns to enable feature discoverability and reuse.
  • Collaborate with ML engineers and data scientists to operationalize features into training pipelines.

Model Training & MLOps Support
  • Support model training workflows, including dataset preparation and scheduled refreshes.
  • Ensure training datasets and features are reproducible, traceable, and auditable.
  • Integrate data pipelines into CI/CD workflows; support version control, testing, and deployment of data assets.
  • Monitor pipeline health, data freshness, and downstream impact on ML/AI systems.

Required Skills & Experience
5+ years of hands-on data engineering experience in a cloud environment.
Core Technologies
  • Python - strong proficiency for data processing and pipeline development.
  • SQL - advanced skills with hands-on Snowflake transformation experience.
  • Snowflake - ELT pipeline design, schema optimization, performance tuning, cost management.
  • PostgreSQL - experience with querying, data modeling, and analytics; familiarity with SQL Server to PostgreSQL migration a plus.
  • AWS - S3, Glue, Athena, Snowflake integration, and managed relational databases (e.g., Aurora, RDS).
  • Apache Iceberg / S3 Tables - familiarity with open table format ecosystems.
  • Streaming ingestion tools (e.g., Kinesis, Kafka, or equivalent).
  • Workflow orchestration tools (e.g., Airflow, Step Functions, or equivalent).

Pipeline & Data Engineering
  • Experience with full loads, incremental loads, append-only pipelines, change-based processing, and SCDs.
  • Data validation, reconciliation, error handling, and restart/recovery patterns.
  • Data modeling for analytics, ML/AI, and downstream application use cases.
  • Ability to evaluate pipeline design trade-offs across performance, cost, reliability, and maintainability.

DevOps & Engineering Practices
  • Structured SDLC experience with CI/CD pipelines for data and ML workflows.
  • API-based and event-driven data integration patterns.
  • Distributed data processing environments.

ML/AI Data Foundations
  • Understanding of data requirements for ML/AI workloads.
  • Experience preparing training datasets and features from enterprise data lakes.
  • Familiarity with reproducibility, dataset versioning, and data lineage concepts.
  • Familiarity with GenAI concepts relevant to data engineering, such as embedding pipelines, vector databases, retrieval-augmented generation (RAG) data flows, or prompt-driven data processing - including awareness of data security and privacy considerations when working with LLMs.

Education
Bachelor's degree in Computer Science, Data Engineering, Information Systems, or a related technical field. Equivalent professional experience will be considered.
Location: Remote
Status: Full time position with full company benefits.
NOTICE: EO/AA/VEVRAA/Disabled Employer - Federal Contractor. FEI Systems participates in E-Verify, a federal program that enables employers to verify the identity and employment eligibility of all persons hired to work in the United States by providing the Social Security Administration (SSA) and, if necessary, the Department of Homeland Security (DHS), with information from each new employee's Form I-9 to confirm work authorization. For more information on E-Verify, please contact DHS at (888) 464-4218.
Applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, age, marital status, political affiliation, disability, or genetic information, except where it relates to a bona fide occupational qualification or requirement. FEI Systems creates an Affirmative Action Plan on an annual basis. Pursuant to federal law, the portions of FEI Systems' Affirmative Action Program that relate to Section 503 (Persons with Disabilities) and/or Section 4212 (Protected Veterans), are available for inspection upon request by applicants and employees during FEI Systems' normal business hours.
Equal Opportunity Employer
This employer is required to notify all applicants of their rights pursuant to federal employment laws. For further information, please review the Know Your Rights notice from the Department of Labor.

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