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Senior Ai Data Trainer Jobs in Riverside, CA (NOW HIRING)

MegazoneCloud US

Sr. Solutions Architect AI

Irvine, CA · On-site

... data pipelines, feature stores, model training, vector databases, and real-time inference. • Own ... Define best practices for responsible AI, data quality, and security, serving as the final point of ...

IT America Inc

Sr. Data Engineer (AI + AWS)

Irvine, CA · On-site

$122K - $147K/yr

Position: Sr. Data Engineer (AI + AWS) Location: Irvine/LA, CA (Onsite) Duration: Long term ... datasets for AI/ML model training and inference. * Deploy and manage containerized data ...

Armaninollp

Senior Data & AI Platform Engineer

Irvine, CA

$72.25 - $96.50/hr

This is a senior engineering role. You will architect, operate, and continuously improve cloud data ... training. Armanino expressly prohibits any form of workplace harassment based on race, color ...

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Senior Ai Data Trainer information

See Riverside, CA salary details

$25.6K

$80.7K

$142.4K

How much do senior ai data trainer jobs pay per year?

As of Aug 19, 2026, the average yearly pay for senior ai data trainer in Riverside, CA is $80,697.00, according to ZipRecruiter salary data. Most workers in this role earn between $58,400.00 and $104,300.00 per year, depending on experience, location, and employer.

What is a senior AI data trainer?

Senior AI Data Trainers are professionals who oversee the creation, curation, and labeling of data used to train artificial intelligence models. They ensure that data is accurately annotated and aligned with the requirements of the machine learning project, often supervising and mentoring junior data trainers. Their responsibilities also include developing guidelines, maintaining data quality standards, and collaborating with data scientists and engineers to improve AI model performance. Senior AI Data Trainers play a critical role in the success of AI initiatives by ensuring high-quality, well-labeled datasets.

What are the key skills and qualifications needed to thrive as a senior AI data trainer?

To thrive as a Senior AI Data Trainer, you need a strong background in data annotation, machine learning concepts, and quality assurance, typically supported by a relevant degree and prior experience in AI training projects. Familiarity with annotation tools, data labeling platforms, and version control systems is commonly required, along with knowledge of Python or similar scripting languages. Excellent attention to detail, communication, and problem-solving skills help ensure accurate data labeling and effective collaboration with cross-functional teams. These skills are crucial for building high-quality datasets that directly impact the performance and reliability of AI models.

What are some common challenges faced by senior AI data trainers when ensuring data quality for machine learning models?

Senior AI Data Trainers often encounter challenges such as managing large and diverse datasets, maintaining labeling consistency, and identifying subtle biases that could affect model performance. They must also coordinate with data engineers and machine learning teams to validate data accuracy and relevance. Addressing these challenges requires strong attention to detail, effective communication skills, and the ability to implement quality assurance processes throughout the data annotation lifecycle.

What is the difference between Senior Ai Data Trainer vs Data Analyst?

AspectSenior Ai Data TrainerData Analyst
Required CredentialsBachelor's or higher in CS, Data Science, or related; experience with AI modelsBachelor's or higher in Statistics, Data Science, or related; proficiency in data analysis tools
Work EnvironmentAI development teams, tech companies, research labsBusiness, finance, healthcare, or tech sectors; data-driven departments
Employer & Industry UsageAI-focused companies, tech startups, research institutionsVarious industries including finance, marketing, healthcare

While both roles involve working with data, a Senior Ai Data Trainer specializes in preparing and refining datasets for AI models, often requiring knowledge of machine learning and AI frameworks. In contrast, a Data Analyst focuses on interpreting data to generate insights for business decisions. The roles overlap in data handling but differ in technical focus and application.

What are the most commonly searched types of Ai Data Trainer jobs in Riverside, CA?

The most popular types of Ai Data Trainer jobs in Riverside, CA are:

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Senior Ai Data Trainer jobs near you

Sr. Solutions Architect AI

MegazoneCloud US

Irvine, CA • On-site

Full-time

Re-posted 4 days ago

Job description

Job Summary:
Megazone Cloud is seeking a Director of AI & Databricks Solutions to lead their AI practice and act as a technical authority for clients. The role focuses on architecting and overseeing the implementation of AI/ML platforms, guiding teams, and driving strategic relationships within the Databricks ecosystem.
Responsibilities:
• Lead Technical Strategy & Design: Architect and oversee the implementation of enterprise-scale AI/ML and GenAI platforms across AWS, Azure, GCP, and Databricks.
• Be the Client-Facing Expert: Lead discovery workshops to surface high-impact use cases, translate complex business requirements into architectural roadmaps, and present ROI models to executive stakeholders.
• Architect the Future: Design reference architectures on Databricks covering data pipelines, feature stores, model training, vector databases, and real-time inference.
• Own the Ecosystem: Drive strategic relationships with AWS, Azure, GCP, and Databricks, ensuring our offerings leverage the latest innovations in GenAI and MLOps.
• Set the Standard: Define best practices for responsible AI, data quality, and security, serving as the final point of escalation for complex technical challenges.
• Mentor and Multiply: Lead and grow a multidisciplinary team of engineers and data scientists, acting as a "force multiplier" through technical guidance and design reviews.
• Market Leadership: Represent Megazone Cloud at industry conferences, publish white papers, and position the firm as a premier leader in applied-AI innovation.
Qualifications:
Required:
• 8-12+ years of experience in data science, AI, and data ecosystems, with at least 5 years leading cross-functional technical teams.
• Deep, hands-on expertise with the Databricks stack and a proven track record of integrating Databricks into complex client environments.
• 2+ years of progressive experience in cloud architecture or solutions engineering across AWS, Azure, or GCP.
• Proven ability to build, manage, and mentor technical teams while managing multi-faceted projects.
• Exceptional skills in presenting to executive audiences and translating business needs into technical designs.
• Bachelor’s degree in Computer Science, Data Science, or a related field (Master’s or PhD preferred).
• A startup mentality, a strategic approach to problem-solving, and a genuine thirst for knowledge.
Preferred:
• Relevant high-level certifications (e.g., Databricks Machine Learning Professional, AWS ML Specialty, Azure AI Engineer, or Google Professional ML Engineer).
• Experience in a Professional Services or consulting environment.
Company:
AWS, DataBricks, Snowflake and GCP Partner of the Year! AI-Native Transformation, Application Modernization, Amazon Connect, Cloud Migrations, Data Analytics and Insights. Founded in , the company is headquartered in Fairport, New York, US, , with a team of 1001-5000 employees. The company is currently Late Stage.

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