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Ai Data Annotation Remote Jobs in Maryland (NOW HIRING)

Deep knowledge in AI, data mining, data evaluation, and proficiency in compiling an effective and ... We embrace a remote-first culture through our Flexible Workplace. Most employees hold Home-Flex ...

Deep knowledge in AI, data mining, data evaluation, and proficiency in compiling an effective and ... We embrace a remote-first culture through our Flexible Workplace. Most employees hold Home-Flex ...

Senior Manager, Master Data Delivery Towson, MD/ Remote based in the USA Come build your career. It ... Utilize technical expertise in Generative AI, Data Modeling, SQL, Python, Alteryx or other data ...

New

AI Legal Counsel - Remote

Baltimore, MD ยท Remote

$90 - $130/hr

Remote Job Summary: We are seeking seasoned in-house transactional attorneys for a part-time role ... Collaborate with product and research teams to refine data, guidelines, and best practices for AI ...

Legal AI Trainer - Remote

Baltimore, MD ยท Remote

$90 - $150/hr

Remote We are seeking seasoned Funds Attorneys for a part-time role at the forefront of legal AI ... Collaborate with product and research teams to refine data, guidelines, and best practices for AI ...

$70K - $100K/yr

... AI capabilities. This remote role welcomes candidates anywhere in Canada and the US. Travel is ... Guide cross-functional teams of data scientists and engineers to build and deploy proof-of-concepts ...

Remote We are seeking seasoned M&A attorneys for a part-time role at the forefront of legal AI ... Collaborate with product and research teams to refine data, guidelines, and best practices for AI ...

Sr. Data Analytics Engineer

Baltimore, MD ยท 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 ...

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Ai Data Annotation Remote information

What is an AI data annotation remote?

An AI Data Annotation Remote job involves labeling, tagging, or categorizing data used to train artificial intelligence models. Annotators work with text, images, audio, or video to ensure machine learning algorithms receive accurate and high-quality input. This role is performed remotely, allowing flexibility in work location and schedule. Attention to detail, consistency, and familiarity with annotation tools are essential skills for this job.

What does a typical day look like for someone working remotely in AI data annotation?

A typical day for a remote AI Data Annotation worker involves reviewing and labeling various types of data such as images, text, or audio according to specific guidelines provided by the employer or project lead. You may use specialized annotation software and work through batches of data while following quality standards and deadlines. Periodic team check-ins or virtual meetings help clarify instructions, address questions, and monitor progress. While most of the work is independent, communication with supervisors or quality assurance teams is important to ensure that data labeling is consistent and accurate.

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

To thrive as an AI Data Annotation Remote worker, you need strong attention to detail, familiarity with data labeling processes, and a basic understanding of machine learning concepts, often supported by a high school diploma or relevant experience. Familiarity with data annotation platforms such as Labelbox, Supervisely, or AWS SageMaker Ground Truth is typically required, and certifications in data annotation or AI may be advantageous. Strong time management, the ability to work independently, and clear communication skills are valuable in this remote role. These abilities ensure accurate and efficient data labeling, which is critical for training reliable AI models.

What are the most commonly searched types of Ai Data Annotation jobs in Maryland?

The most popular types of Ai Data Annotation jobs in Maryland are:

What are popular job titles related to Ai Data Annotation Remote jobs in Maryland?

For Ai Data Annotation Remote jobs in Maryland, the most frequently searched job titles are:

What job categories do people searching Ai Data Annotation Remote jobs in Maryland look for?

The top searched job categories for Ai Data Annotation Remote jobs in Maryland are:

What cities in Maryland are hiring for Ai Data Annotation Remote jobs?

Cities in Maryland with the most Ai Data Annotation Remote job openings:

Infographic showing various Ai Data Annotation Remote job openings in Maryland as of August 2026, with employment types broken down into 1% As Needed, 83% Full Time, 13% Part Time, and 3% Contract. Highlights an 85% Physical, 4% Hybrid, and 11% Remote job distribution.

Data Engineer - ML/AI Data Platform (Remote)

Columbia, MD โ€ข On-site, Remote

FEI Systems
IT Servicesย โ€ขย 501 - 1,000 employees

$111K - $133K/yr

Full-time

Re-posted 21 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.