Remote AI Data Specialist Jobs
Remote AI Data Specialist jobs are in active demand across the U.S., with remote-first firms and distributed teams hiring for roles in AI, machine learning, and data annotation across technology, healthcare, and financial services. Employers hiring remotely right now include BlackRock, Enlyte, and BV Teck. Find a role that fits below and apply directly.
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Job Title: Data Engineering Specialist – AI
Location: 100% Remote Role
Position Type: Full-time (Only W2 candidates)
Salary Range: $100,000–$150,000 Annually
Experience Required: 6+ years
Sponsorship: U.S. Citizens, Green Card Holders, EAD Holders, and H-1B transfer candidates are encouraged to apply. We are unable to sponsor new H-1B visa petitions for this position.
Job Summary
We are seeking an Data Engineering Specialist – AI to build and operate the large-scale data systems that power modern AI training and evaluation pipelines. The role combines deep data engineering expertise with a strong understanding of AI workloads, focusing on ingestion, transformation, quality assurance, lineage, and high-throughput delivery of data to training jobs across diverse modalities. The ideal candidate has experience operating petabyte-scale data systems, strong software engineering fundamentals, and clear understanding of how data infrastructure choices propagate into model quality and training efficiency.
Required Qualifications
- 6+ years of data engineering experience, with significant work supporting ML or AI workloads.
- Strong proficiency in Python and at least one JVM or systems language.
- Deep experience with modern data processing frameworks such as Spark, Ray, or Beam.
- Hands-on experience operating petabyte-scale storage and pipeline systems.
- Experience with multimodal datasets at large scale.
- Familiarity with data quality tooling and dataset evaluation methodology.
- Exposure to privacy-preserving data systems and regulated data handling.
- Open-source contributions to data infrastructure projects.
- Experience supporting frontier model training pipelines.
How to Apply
Would you like to know more about this opportunity?
For immediate consideration, please send your resume to jaya@bvteck.com or contact us at (908) 505-3545. Learn more about Bright Vision Technologies at www.bvteck.com.
Bright Vision Technologies is an Equal Opportunity Employer.
Equal Employment Opportunity (EEO) Statement
Bright Vision Technologies (BV Teck) is committed to equal employment opportunity (EEO) for all employees and applicants without regard to race, color, religion, sex, sexual orientation, gender identity or expression, national origin, age, genetic information, disability, veteran status, or any other protected status as defined by applicable federal, state, or local laws. This commitment extends to all aspects of employment, including recruitment, hiring, training, compensation, promotion, transfer, leaves of absence, termination, layoffs, and recall.
BV Teck expressly prohibits any form of workplace harassment or discrimination. Any improper interference with employees' ability to perform their job duties may result in disciplinary action up to and including termination of employment.
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Job Title: Data Engineering Specialist – AI
Location: 100% Remote Role
Position Type: Full-time (Only W2 candidates)
Salary Range: $100,000–$150,000 Annually
Experience Required: 6+ years
Sponsorship: U.S. Citizens, Green Card Holders, EAD Holders, and H-1B transfer candidates are encouraged to apply. We are unable to sponsor new H-1B visa petitions for this position.
Job Summary
We are seeking an Data Engineering Specialist – AI to build and operate the large-scale data systems that power modern AI training and evaluation pipelines. The role combines deep data engineering expertise with a strong understanding of AI workloads, focusing on ingestion, transformation, quality assurance, lineage, and high-throughput delivery of data to training jobs across diverse modalities. The ideal candidate has experience operating petabyte-scale data systems, strong software engineering fundamentals, and clear understanding of how data infrastructure choices propagate into model quality and training efficiency.
Required Qualifications
- 6+ years of data engineering experience, with significant work supporting ML or AI workloads.
- Strong proficiency in Python and at least one JVM or systems language.
- Deep experience with modern data processing frameworks such as Spark, Ray, or Beam.
- Hands-on experience operating petabyte-scale storage and pipeline systems.
- Experience with multimodal datasets at large scale.
- Familiarity with data quality tooling and dataset evaluation methodology.
- Exposure to privacy-preserving data systems and regulated data handling.
- Open-source contributions to data infrastructure projects.
- Experience supporting frontier model training pipelines.
How to Apply
Would you like to know more about this opportunity?
For immediate consideration, please send your resume to jaya@bvteck.com or contact us at (908) 505-3545. Learn more about Bright Vision Technologies at www.bvteck.com.
Bright Vision Technologies is an Equal Opportunity Employer.
Equal Employment Opportunity (EEO) Statement
Bright Vision Technologies (BV Teck) is committed to equal employment opportunity (EEO) for all employees and applicants without regard to race, color, religion, sex, sexual orientation, gender identity or expression, national origin, age, genetic information, disability, veteran status, or any other protected status as defined by applicable federal, state, or local laws. This commitment extends to all aspects of employment, including recruitment, hiring, training, compensation, promotion, transfer, leaves of absence, termination, layoffs, and recall.
BV Teck expressly prohibits any form of workplace harassment or discrimination. Any improper interference with employees' ability to perform their job duties may result in disciplinary action up to and including termination of employment.
VhV2MFRl7N
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Find JobsRemote AI Data Specialist Job Market
Who's Hiring
Top Industries Hiring
- Education
- Technology & Software
- Insurance
- Automotive
What Employers Look For
The qualifications that appear most often in remote AI data specialist jobs.
- Bachelor's degree in data science, computer science, linguistics, or a related field
- Proficiency with data annotation platforms such as Scale AI, Labelbox, or CVAT
- Experience with Python for data preprocessing, cleaning, and pipeline scripting
- Familiarity with machine learning concepts including model training, evaluation, and feedback loops
- Strong attention to detail and demonstrated ability to apply complex labeling guidelines consistently
- Experience with SQL or NoSQL databases for querying and managing large datasets
Tips for Your Remote AI Data Specialist Job Search
Apply early to remote roles that fit
Migrate Mate lists remote ai data specialist openings from across the U.S. in one place, so you can find roles that match your skills and apply directly without sifting through mixed results. Early applicants on remote roles move through review queues faster.
Build a portfolio of annotation and evaluation work
Remote employers want proof you can deliver quality data work without supervision. Document real projects: data labeling runs, AI output evaluation tasks, or quality audits. Show your accuracy rate, the tools you used, and the scale of the dataset.
Sharpen your async written communication skills
Remote ai data specialist teams run on written communication. Practice writing concise status updates, clear bug reports for annotation errors, and structured feedback on model outputs. Employers assess this in take-home tasks and async interview rounds.
Target remote-first firms with active AI pipelines
Companies that have operated remotely from their founding are set up to onboard ai data specialists without in-office onboarding. Look for AI product companies, machine learning platforms, and enterprise software firms with dedicated data operations functions.
Remote AI Data Specialist Jobs: Frequently Asked Questions
How do I get a remote ai data specialist job?
Remote ai data specialist roles go to candidates who can demonstrate self-direction, clear async written communication, and hands-on experience with data labeling, quality evaluation, or model training pipelines. Remote employers screen heavily for comfort with distributed workflows and tools like Slack, Jira, and collaborative annotation platforms. A portfolio showing real annotation work, data quality projects, or AI evaluation tasks gives you a concrete edge over candidates with credentials alone.
Which companies hire remote ai data specialists?
Remote ai data specialist roles are posted by BlackRock, Enlyte, and BV Teck and others right now, based on current remote listings on Migrate Mate as of September 2026. These include remote-first technology firms, AI product companies, and distributed teams in sectors such as enterprise software, healthcare AI, and financial data services.
Can you get a remote ai data specialist job with no experience?
Yes, but remote entry-level roles are harder to land because employers expect you to work independently from day one without in-person oversight. Your best path is to complete publicly available data annotation or AI evaluation projects, contribute to open datasets, and document the results. Smaller AI startups and contractor-based remote teams are the most likely to hire entry-level candidates who can show real output.
Do you need a degree for remote ai data specialist jobs?
Not always. Remote employers in this field weigh demonstrated skills, annotation accuracy, and familiarity with AI workflows more heavily than a specific degree. Candidates who can show completed data labeling work, knowledge of quality assurance processes for training data, and comfort with remote collaboration tools often move forward regardless of educational background.
Which industries hire the most remote ai data specialists?
Remote ai data specialist roles concentrate in Education, Technology & Software, and Insurance, based on current remote listings on Migrate Mate as of September 2026. Those sectors rely on distributed teams to handle data annotation, model evaluation, and AI quality work that can be done fully asynchronously and at scale.
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