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Remote Ai Data Trainer Jobs in Renton, WA (NOW HIRING)

OTSI

AI & Data Solutions Architect

Seattle, WA · Remote

Seattle (Remote, some travel required) We are seeking a highly technical, client-facing AI & Data Solutions Architect to lead enterprise engagements, drive presales strategy, and facilitate ...

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

As of Jun 26, 2026, the average hourly pay for remote ai data trainer in Renton, WA is $35.14, according to ZipRecruiter salary data. Most workers in this role earn between $22.45 and $40.00 per hour, depending on experience, location, and employer.

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

To thrive as a Remote AI Data Trainer, you need strong analytical skills, attention to detail, and experience in data annotation or evaluation, often supported by a background in computer science, linguistics, or a related field. Familiarity with data labeling platforms, AI training tools, and sometimes programming languages like Python is typically required. Excellent communication, self-motivation, and the ability to work independently are key soft skills for remote collaboration and consistent performance. These skills ensure high-quality data preparation, accurate AI model training, and effective teamwork in distributed environments.

What is a Remote AI Data Trainer?

A Remote AI Data Trainer is a professional who works from a remote location to help train artificial intelligence systems by preparing, labeling, and reviewing data sets. This role often involves annotating images, text, audio, or video to ensure AI models learn correctly from quality data. Remote AI Data Trainers may also evaluate the performance of AI outputs and provide feedback for improvements. They typically work with machine learning engineers and data scientists to support the development of accurate and ethical AI systems.

What are some typical challenges Remote AI Data Trainers face when working with diverse datasets?

Remote AI Data Trainers often work with datasets that vary greatly in structure, quality, and subject matter. One common challenge is ensuring consistency and accuracy while annotating or labeling data, especially when guidelines are complex or ambiguous. Additionally, working remotely requires strong communication skills to collaborate effectively with data scientists, project managers, and other trainers. Staying organized and managing time efficiently are crucial since trainers might juggle multiple projects or deadlines. Regular feedback sessions and adherence to detailed documentation help overcome these challenges and maintain high-quality output.
What job categories do people searching Remote Ai Data Trainer jobs in Renton, WA look for? The top searched job categories for Remote Ai Data Trainer jobs in Renton, WA are:
What cities near Renton, WA are hiring for Remote Ai Data Trainer jobs? Cities near Renton, WA with the most Remote Ai Data Trainer job openings:
Remote Ai Data Trainer jobs near you
Infographic showing various Remote Ai Data Trainer job openings in Renton, WA as of June 2026, with employment types broken down into 1% As Needed, 75% Full Time, 21% Part Time, 2% Contract, and 1% Nights. Highlights an 65% Physical, 4% Hybrid, and 31% Remote job distribution, with an average salary of $73,096 per year, or $35.1 per hour.

AI & Data Solutions Architect

OTSI

Seattle, WA • Remote

Full-time

Posted 27 days ago

Job description

OTSI (Object Technology Solutions, Inc) has an immediate opening for an AI & Data Solutions Architect Location: Seattle (Remote, some travel required) We are seeking a highly technical, client-facing AI & Data Solutions Architect to lead enterprise engagements, drive presales strategy, and facilitate architecture design sessions. You will serve as a trusted advisor to our clients, architecture complex data modernization and AI adoption strategies. While this role heavily emphasizes client interaction, executive presentation, and architectural design, it requires a strong technical practitioner who is fully capable of engaging in hands-on development and technical problem-solving to support global delivery teams and ensure project success.

Key Responsibilities Strategic Presales & Solution Architecture: Act as the lead technical strategist during sales cycles. Partner with Sales to shape deal strategy, facilitate architecture design sessions with C-suite stakeholders, define solution scope, and build compelling business and technical narratives. End-to-End Architecture Design: Architect scalable, cloud-native software solutions and modern data platforms (e.g

Microsoft Fabric, Databricks, Snowflake) aligned with enterprise analytics and AI initiatives. Delivery Oversight & Hands-On Execution: Provide technical leadership to global development and data engineering teams. Serve as the definitive technical escalation point who can configure systems, develop scripts, or build proofs-of-concept to ensure the delivery of critical project milestones.

Advanced AI Strategy: Design robust AI/ML solutions that advance beyond foundational LLM integrations. Guide clients in implementing Agentic AI workflows, autonomous orchestration, and secure enterprise integrations utilizing frameworks such as the Model Context Protocol (MCP). Governance & Optimization: Ensure architectural consistency, quality, and strict adherence to enterprise AI governance and security frameworks throughout the SDLC.

Optimize cloud architectures across Azure, AWS, and GCP to balance innovation, performance, and cost efficiency. Research & Development: Stay up to date with AI/ML technologies, advancements, and trends. Provide insights to guide internal R&D efforts on company products, tools, and accelerators outside of client engagements.

Required Skills: Consulting, Presales & Leadership Client Engagement: 8+ years in client-facing presales, consulting, or solution architecture roles. Proven ability to facilitate executive discussions, translate complex technical concepts into clear business value, and drive consensus among enterprise stakeholders. Executive Presentation: Exceptional white boarding and communication skills.

Demonstrated capability to dynamically design and articulate modern data architectures for both engineering leadership and business executives. Global Collaboration: Experience mentoring development teams and partnering seamlessly across a global delivery model to ensure the successful hand off, translation, and execution of defined architectures. Required Skills: Core Technical Expertise Cloud & Data Platforms: 7+ years designing cloud-native architectures (Azure, AWS, or GCP).

Deep architectural knowledge of modern data platforms (preferably Databricks or Microsoft Fabric) and distributed compute frameworks (Apache Spark). Applied AI & Machine Learning: Strong architectural experience designing AI/ML solutions, vector databases, and RAG architectures. Expertise in developing Agentic AI systems and workflow automation utilizing frameworks such as LangChain and the Model Context Protocol (MCP).

Practitioner Capability: Retained hands-on engineering proficiency with a strong command of Python and SQL, alongside experience in highly scalable backend languages like Java or Go. Fully capable of executing detailed technical work and navigating the modern SDLC. AI Productivity & Infrastructure: Active utilization of AI productivity tools (e.g., GitHub Copilot, Claude) to accelerate development

Solid understanding of containerization (Docker, Kubernetes) and CI/CD pipelines to ensure the reliable, scalable deployment of AI models into production environments. Enterprise Integration: Expertise in designing robust data pipelines, semantic models, and API integrations that seamlessly connect AI capabilities within complex, legacy enterprise environments (e.g., SAP, Oracle).

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