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Ai Data Training Jobs (NOW HIRING)

Schonfeld

AI Data Engineer

New York, NY · On-site

$125K - $150K/yr

Implement data versioning, lineage tracking, and observability for AI training and inference pipelines. * Optimize data delivery for low-latency AI interactions and high-throughput batch processing.

Innovative Solutions

AI Data Architect

Rochester, NY · Remote

$65.25 - $84/hr

As a Data/AI Architect, you'll design and build data-driven cloud architectures on AWS -- from S3 ... Design SageMaker ML pipelines for training, Model Registry, and inference * Lead data discovery ...

TWG Global AI

Associate AI Data Scientist

Santa Monica, CA · On-site

$120K - $130K/yr

We prioritize responsible data and AI practices to ensure ethical standards and regulatory ... Participate in training and development opportunities to enhance skills and knowledge. Requirements ...

Innovative Solutions

AI Data Architect

Rochester, NY · On-site +1

$150K - $200K/yr

As a Data/AI Architect, you'll design and build data-driven cloud architectures on AWS - from S3 ... Design SageMaker ML pipelines for training, Model Registry, and inference * Lead data discovery ...

Innovative Solutions

AI Data Architect

$150K - $200K/yr

As a Data/AI Architect, you'll design and build data-driven cloud architectures on AWS - from S3 ... Design SageMaker ML pipelines for training, Model Registry, and inference * Lead data discovery ...

Trustwell

Lead AI & Data Scientist

$150K - $170K/yr

Lead AI & Data Scientist FLSA: Full Time | Exempt | Salaried | Remote (US) Reports to: Chief ... Experience creating internal AI usage policies, review boards, enablement materials, training ...

eTeam

AI & Data - Data Engineer

Seattle, WA · On-site

$130K - $156K/yr

... training and inference. • Implement data quality tests, documentation, and lineage in DBT • ... AI/Data Science) team to provide feature ready datasets. Qualifications : Required : • Hands-on ...

HP Development Company, L.P.

AI Data Scientist

Spring, TX · On-site

$130K - $205K/yr

We also serve as HP's AI Center of Excellence, providing consulting assistance, reuseable components and frameworks, and training to other teams across the company. As a Data Scientist focused on ...

Diverse Lynx

Principal AI Data Architect

Redmond, WA · On-site

Own the ML and LLMOps data infrastructure: training data curation pipelines, feature engineering ... Conversational AI Platforms - low-latency, context-rich data APIs that power chatbots, voice ...

Hp

AI Data Scientist

Spring, TX · On-site

$130K - $205K/yr

We also serve as HP's AI Center of Excellence, providing consulting assistance, reuseable components and frameworks, and training to other teams across the company. As a Data Scientist focused on ...

GE HealthCare

Data Manager - AI Development

$94K - $141K/yr

Summary The Data Manager - AI Development is a key role within the AI Development team responsible ... Data segregation between training, holdout, and testing datasets * Data preparation and inclusion ...

C the Signs

AI Data Engineer

New York, NY · Remote

$117K - $140K/yr

... training and refinement Key Responsibilities * Collaborate with data scientists and machine ... Joining C the Signs is not just about building AI; it's about shaping the future of healthcare. If ...

C the Signs

AI Data Engineer

Boston, MA · On-site +1

$124K - $149K/yr

... training and refinement Key Responsibilities * Collaborate with data scientists and machine ... Joining C the Signs is not just about building AI; it's about shaping the future of healthcare. If ...

Saviance

AI Data Governance (SME)

Advise on de-identification methodologies (Safe Harbor, Expert Determination) for AI training datasets * Partner with legal, compliance, IT, clinical, and data science teams to align governance ...

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Ai Data Training information

What are the key skills and qualifications needed to thrive as an AI Data Trainer, and why are they important?

To thrive as an AI Data Trainer, you need a solid understanding of data annotation, machine learning fundamentals, and attention to detail, often backed by experience in data science or a related field. Familiarity with data labeling tools, annotation platforms, and version control systems is typically required. Strong analytical thinking, communication skills, and the ability to follow complex guidelines set top performers apart in this role. These skills ensure that high-quality, accurate datasets are produced to effectively train and improve AI models.

What is the difference between Ai Data Training vs Data Analyst?

AspectAi Data TrainingData Analyst
Required CredentialsDegree in Computer Science, Data Science, or related fields; knowledge of AI/ML frameworksDegree in Statistics, Mathematics, or related fields; proficiency in data analysis tools
Work EnvironmentTech companies, AI startups, research labsBusiness, finance, healthcare, and other industries
Employer & Industry UsagePrimarily in AI development and machine learning projectsAcross various sectors analyzing data to inform decisions

Ai Data Training involves preparing and labeling data for AI models, focusing on machine learning algorithms. Data Analysts interpret data to generate insights for business decisions. While both roles work with data, Ai Data Training is more technical and model-focused, whereas Data Analysts focus on analysis and reporting.

What is AI data training?

AI data training refers to the process of teaching artificial intelligence systems, such as machine learning models, to recognize patterns and make decisions by feeding them large amounts of labeled data. This involves collecting, annotating, and preprocessing data so that the AI can learn from examples and improve its performance over time. Data trainers play a crucial role in ensuring that the data used is accurate, diverse, and relevant to the AI's intended tasks. Effective AI data training helps models become more accurate, reliable, and capable of handling real-world scenarios.

What are some common challenges faced in AI Data Training roles, and how can they be effectively managed?

Professionals in AI Data Training often encounter challenges such as ensuring data accuracy, managing large and potentially unstructured datasets, and maintaining consistency in labeling. These challenges can be managed through rigorous quality control checks, adopting clear annotation guidelines, and utilizing collaborative tools that streamline the review process. Being detail-oriented and communicating effectively with data scientists and engineers also helps in resolving ambiguities and improving overall data quality.
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Ai Data Training jobs near you
Infographic showing various Ai Data Training job openings in the United States as of June 2026, with employment types broken down into 37% Full Time, 62% Part Time, and 1% Contract. Highlights an 66% Physical, 3% Hybrid, and 31% Remote job distribution.

AI Data Infrastructure Engineer

Bright Vision Technologies

San Ramon, CA • Remote

$100K - $150K/yr

Full-time

This job post has expired 2 days ago. Applications are no longer accepted.

Job description

Bright Vision Technologies is a forward-thinking software development company dedicated to building innovative solutions that help businesses automate and optimize their operations. We leverage cutting-edge technologies to create scalable, secure, and user-friendly applications.
As we continue to grow, we’re looking for a skilled AI Data Infrastructure Engineer to join our dynamic team and contribute to our mission of transforming business processes through technology.
This is a fantastic opportunity to join an established and well-respected organization offering tremendous career growth potential.
Job Title: AI Data Infrastructure Engineer
Location: 100% Remote (Continental United States)
Position Type: In-house Bright Vision Technologies SOW engagement (no third-party client or vendor)
Salary: $100K - $150K
Experience: 6+ years
Sponsorship: No new H1B sponsorship available. H1B transfers welcomed for qualified candidates.
Employment Type: Full-time, direct W2 with Bright Vision Technologies (no C2C, no 1099, no third-party)
Engagement: Long-term, multi-year, aligned to the Bright Vision SOW delivery roadmap
Compensation: Competitive base salary commensurate with experience, plus benefits.
Employment Terms & Visa Policy
This is a 100% remote, full-time, direct W2 position with Bright Vision Technologies.
This role is part of Bright Vision Technologies’ in-house Statement of Work (SOW) engagement. The client, end customer, and employer for this position is Bright Vision Technologies — there is no third-party client, vendor, or implementation partner involved.
We do not engage in C2C, 1099, or third-party arrangements for this role.
BUT STRICTLY NO C2C/1099/3RD PARTY COMPANIES. ALL OUR ROLES ARE W2 AND NO 3RD PARTY BROKERING PLEASE.
Candidates must be willing to work directly as a full-time W2 employee of Bright Vision Technologies and contribute to our in-house SOW deliverables.
No new H1B sponsorship is available for this role.
However, candidates who are currently on a valid H1B visa and require a transfer are welcome to apply. We will support H1B transfers for qualified candidates.
For every role, a technical coding assessment is mandatory. Please apply only if you are confident in your technical abilities and hands-on experience.
Job Summary
We are seeking an AI Data Infrastructure Engineer 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.
Key Responsibilities
  • Design and operate large-scale data pipelines supporting AI training, evaluation, and continual improvement workflows.
  • Build ingestion systems for diverse modalities including text, image, audio, video, and structured signals.
  • Implement data cleaning, deduplication, filtering, and quality assurance at petabyte scale.
  • Develop dataset versioning, lineage, and provenance tracking systems suitable for reproducible training.
  • Build high-throughput data loading systems that maximize GPU utilization during training.
  • Implement labeling workflows, active learning pipelines, and human-in-the-loop data improvement systems.
  • Design storage architectures balancing cost, throughput, and latency across data tiers.
  • Build evaluation dataset construction pipelines with strict integrity and contamination controls.
  • Implement data privacy, redaction, and consent enforcement throughout the pipeline.
  • Collaborate with ML researchers and engineers to align data systems with model development needs.
  • Drive observability of data quality, drift, and pipeline health across the AI data estate.
  • Optimize cost and performance through compression, format selection, and caching strategies.
  • Document data systems, schemas, and operational procedures for broad internal use.
  • Stay current with AI data infrastructure research and emerging open-source tools.
Required Qualifications
  • Bachelor’s or Master’s degree in Computer Science or a related field.
  • Six or more 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.
  • Strong understanding of distributed systems, data modeling, and storage formats.
  • Experience with dataset versioning, lineage, and reproducibility for ML workflows.
  • Familiarity with high-throughput data loading for accelerator-based training.
  • Strong software engineering practices including testing, CI/CD, and code review.
  • Excellent communication and cross-functional collaboration skills.
Preferred Qualifications
  • 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 hilda@bvteck.com.
Learn more about Bright Vision Technologies at www.bvteck.com.
We recognize that our people are our strength, and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company.
We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants’ and employees’ religious practices and beliefs, as well as mental health or physical disability needs.
Bright Vision Technologies is an Equal Opportunity Employer, including Disability/Veterans.
Position offered by “No Fee Agency.”
 

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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