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Contract Ai Data Trainer Jobs (NOW HIRING)

3Pillar

AI Data Architect

Charleston, WV · Remote

$65.25 - $84/hr

The resource will architect the system, drive implementation, own the data contracts that agents and AI applications depend on, enforce security and access governance for both human and agent ...

3Pillar

AI Data Architect

$65.25 - $84/hr

The resource will architect the system, drive implementation, own the data contracts that agents and AI applications depend on, enforce security and access governance for both human and agent ...

Carlyle

AI & Data Architect

New York, NY · On-site

$69.75 - $89.75/hr

Architect AI-ready data foundations - semantic layers, contextual metadata, data contracts, and ... training; licenses and/or certifications. The anticipated base salary range for this role is $200 ...

Apple

AI Data Engineer

Cupertino, CA · On-site

$141K - $169K/yr

The AI Data Engineer owns the pipelines, data feeds, and integration infrastructure that ensure AI ... data contracts, and operational runbooks Minimum Qualifications Bachelor's degree in Computer ...

IntraEdge

AI Data Engineer

Detroit, MI · On-site

$113K - $136K/yr

Automate the training and deployment of AI/ML models into production via APIs and microservices. * Monitor and troubleshoot: Implement data observability tools to monitor pipeline health, identify ...

Tiki AI

AI Data Software Engineer

San Francisco, CA · On-site

$134K - $162K/yr

They are seeking an AI Data Software Engineer who will work closely with AI research labs to ... Responsibilities : • Partner with top-tier AI research labs to translate frontier model training ...

Bright Vision Technologies

AI Data Engineer

Westford, MA · Remote

$100K - $150K/yr

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 ...

Apple

AI Data Engineer

Cupertino, CA

$207K - $311K/yr

The AI Data Engineer owns the pipelines, data feeds, and integration infrastructure that ensure AI ... contracts, and operational runbooks Preferred Qualifications Experience with vector databases ...

1 point system

AI Data Engineer

Redmond, WA · On-site

$128K - $154K/yr

Requirement - AI Data Engineer Location- Redmond WA 98052-Hybrid Contract W2 Top 3 Must-Have Hard Skills 1. Reporting & Analytics - 5+ Years * Minimum 5 years of experience designing and developing ...

Braunability

AI Data Architect

Winamac, IN · On-site

$58.75 - $75.50/hr

Build,optimize, andmaintainthe data pipelines that feed BAA's AI solutions, connecting both ... Automate the ingestion and structuring of unstructured data (PDFs, manuals, contracts, emails) to ...

Carlyle

Data & AI Engineer

New York, NY · On-site +1

$125K - $150K/yr

Implement semantic models, data contracts, and analytical/dimensional models that enable trusted ... training; and licenses and/or certifications. The anticipated base salary range for this role is ...

BraunAbility

AI Data Architect

Winamac, IN · On-site

$58.75 - $75.50/hr

Build, optimize, and maintain the data pipelines that feed BAA's AI solutions, connecting both ... Automate the ingestion and structuring of unstructured data (PDFs, manuals, contracts, emails) to ...

STI

AI Data Architect

$65.25 - $84/hr

AI Data Architect Location: Denver, CO/REMOTE This position is for a remote work environment ... NIST AI Framework training or certification

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Contract Ai Data Trainer information

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How much do contract ai data trainer jobs pay per hour?

As of Aug 4, 2026, the average hourly pay for contract ai data trainer in the United States is $31.24, according to ZipRecruiter salary data. Most workers in this role earn between $19.95 and $35.58 per hour, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a contract AI data trainer, and why are they important?

To thrive as a Contract AI Data Trainer, you need strong analytical abilities, attention to detail, and a solid understanding of data labeling and AI concepts, often supported by experience in data annotation or a related field. Familiarity with annotation tools like Labelbox, SuperAnnotate, or Prodigy, as well as basic knowledge of machine learning platforms and data management systems, is typically required. Excellent communication, time management, and adaptability are important soft skills for working with diverse teams and handling variable project requirements. These skills ensure the delivery of high-quality, accurately labeled datasets that are essential for effective AI model training and performance.

What is a contract AI data trainer?

Contract AI Data Trainers are professionals hired on a contractual basis to label, annotate, or curate data used to train artificial intelligence and machine learning models. They help ensure that data sets are accurate, organized, and properly categorized, which is essential for developing effective AI systems. The work can involve text, images, audio, or other data types, and often requires attention to detail and adherence to specific guidelines. Contract AI Data Trainers may work remotely or onsite, and their contracts may vary in length depending on project needs.

What is the difference between Contract Ai Data Trainer vs Data Annotator?

AspectContract Ai Data TrainerData Annotator
CredentialsBasic technical skills, training in AI conceptsMinimal formal credentials, training often provided
Work EnvironmentRemote or on-site, collaborative with AI teamsRemote or on-site, focused on labeling data
Industry UsageUsed in AI development, machine learning projectsUsed in data preparation, dataset creation

Contract Ai Data Trainers and Data Annotators both work with data, but the Trainer focuses on guiding AI models through training and feedback, while Annotators primarily label data. The Trainer typically requires some technical knowledge and works closely with AI teams, whereas Annotators focus on data labeling tasks. Both roles are essential in AI development, but their responsibilities and skill requirements differ.

What are some common challenges faced by contract AI data trainers when working with diverse datasets?

Contract AI Data Trainers often work with a wide range of datasets, which can vary greatly in quality, format, and subject matter. One common challenge is ensuring consistency and accuracy in data labeling across different projects, especially when guidelines or expectations shift between clients. Additionally, trainers may encounter ambiguous data or unclear instructions, requiring strong communication with project managers and other team members to resolve uncertainties. Staying up to date with evolving best practices in data annotation and collaborating effectively in remote or distributed teams are also important aspects of the role.
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Contract Ai Data Trainer jobs near you
Infographic showing various Contract Ai Data Trainer job openings in the United States as of July 2026, with employment types broken down into 73% Full Time, 24% Part Time, and 3% Contract. Highlights an 65% Physical, 3% Hybrid, and 32% Remote job distribution, with an average salary of $64,984 per year, or $31.2 per hour.

AI Data Architect

3Pillar

Charleston, WV • Remote

$65.25 - $84/hr

Full-time

Posted 9 days ago

Job description

3Pillar is an AI transformation partner on a mission to help enterprises build the AI-native products and intelligent agents that will define the next era of business. With teams across North America, Europe, Latin America, and Asia, we work with the most ambitious companies in financial services, healthcare, media, and technology — helping them move faster, modernize boldly, and compete on their own terms. Our HelixAI platform and Helix Pods delivery model put our engineers at the center of real agentic transformation — doing work that is open, portable, and built to last. We are building the future of enterprise AI.
 
AI Data Architect
 
We are looking for an AI Data Architect to design, build, govern, and evolve the single source of truth that powers every AI initiative in our organization.
This platform will serve as the foundational nervous system for conversational AI assistants, dashboard intelligence, autonomous AI agents, RAG-powered applications, predictive ML models, and any AI product we build today or in the future. The resource will architect the system, drive implementation, own the data contracts that agents and AI applications depend on, enforce security and access governance for both human and agent consumers, and continuously monitor and improve the accuracy and reliability of AI outputs that flow from this platform. 
Requirements:
Architect and own the enterprise AI data platform — the unified, governed layer that ingests, transforms, stores, and serves all data consumed by AI systems across the organisation.
Design multi-domain data models (lakehouse, data mesh, event-driven) that are structured from day one to serve AI workloads: clean lineage, versioned schemas, well-documented contracts, and low-latency serving APIs.
Strong exposure to different Data architectures, data lake & data warehouse
Define tools & technologies to develop automated data pipelines, write ETL processes, develop dashboard & report and create insights
Responsibilities
Technical Skills
Primary Skills: Python, SQL, Snowflake/Databricks, AWS (S3, Glue, EKS, Bedrock, Kinesis, Redshift), Docker, Kubernetes, Terraform, GitHub Actions, LangChain, LlamaIndex, LLM APIs (OpenAI, AWS Bedrock, Claude, HuggingFace), (Pinecone, FAISS, ChromaDB, OpenSearch), knowledge graphs (Neo4j).
 
Secondary Skills: MLflow, FastAPI, CI/CD pipelines, observability tooling (CloudWatch, Grafana, or equivalent), data lineage and metadata management platforms.
 
  • 15+ years of hands-on data engineering and architecture experience, alongside building production AI/ML and LLM-era data infrastructure.
  • Strong Experience with either Databricks or Snowflake; experience with both is desirable.
  • Strong data architecture patterns & principles, ability to design secure & scalable data lakes, data warehouse, data hubs, and other event-driven architectures
  • Expertise in designing and writing ETL processes in Python / Java / Scala
  • Own the full data stack: real-time streaming (Kafka, Spark Structured Streaming), batch processing (Databricks, PySpark, Delta Lake), cloud storage and compute (AWS, Azure), and data quality /metadata management.
  • Drive modernisation of legacy pipelines (on-prem ETL, batch DWH) to cloud-native, AI-ready architectures with measurable improvements in cost, latency, and delivery velocity.
  • Proven experience designing enterprise-scale AI data platforms that serve multiple AI consumers —not just one application or pipeline.
  • Hands-on experience with vector stores, semantic models, knowledge graphs, and retrieval infrastructure in production environments.
  • Working knowledge of LLMOps: model serving pipelines, MLflow, CI/CD for AI, automated evaluation, and production monitoring.
     
     
AI Experience
RAG, Vector & Retrieval Infrastructure
Design the retrieval infrastructure that powers RAG-based AI applications: embedding pipelines, vector stores (Pinecone, FAISS, ChromaDB, OpenSearch), chunking strategies, and hybrid retrieval layers combining semantic search with structured queries.
 
Agentic Behaviour Observability & Output Accuracy
Own the observability stack for AI agent behaviour: instrument agents to capture inputs, retrieved context, tool calls, reasoning traces, and outputs — creating a complete audit trail of every agentic action driven by platform data.
Design and operate evaluation frameworks that continuously measure AI output quality: factual accuracy, context faithfulness, retrieval relevance, hallucination rates, and task completion success— across all AI consumers of the platform.
 
Architecture Standards & Engineering Enablement
Define and maintain the reference architecture for the AI data platform — documenting design patterns, data contracts, integration standards, and decision records (ADRs) that all engineering teams follow.
Establish data engineering standards: pipeline testing frameworks, code review practices, CI/CD automation, infrastructure-as-code (Terraform), reusable component libraries, and observability instrumentation.
Benefits

  • Medical Insurance benefits as per company policy. 

  • Dental insurance as per company policy.

  • Vision insurance as per company policy.

  • Employer paid Disability, Life, and AD&D insurance

  • Unlimited PTO 

  • Paid parental leave 

  • 401K

  • Flexible work policy

  • 12 Paid Holidays

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.