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Learning Ai Jobs in Renton, WA (NOW HIRING)

Uw

Assistant Director of Research

Seattle, WA

$140K/yr

This position will also work closely with an EdTech startup team, Colleague AI, to develop product features and conduct research to assess its effects on teacher efficiency and student learning ...

YO AI Labs

AI Trainer - Remote

Seattle, WA · Remote

$80 - $120/hr

No prior AI experience is required. Key Responsibilities ... Create reinforcement learning environments for software engineering tasks. * Design tasks involving ...

YO AI Labs

AI Engineer - Remote

Seattle, WA · Remote

$80 - $120/hr

No prior AI experience is required. Key Responsibilities ... Create reinforcement learning environments for software engineering tasks. * Design tasks involving ...

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How much do learning ai jobs pay per hour?

As of Sep 13, 2026, the average hourly pay for learning ai in Renton, WA is $45.78, according to ZipRecruiter salary data. Most workers in this role earn between $33.27 and $59.47 per hour, depending on experience, location, and employer.

What is a learning AI?

A Learning AI, or Artificial Intelligence that learns, refers to computer systems that can improve their performance over time by analyzing data and experiences. These systems use techniques such as machine learning and deep learning to adapt to new information, recognize patterns, and make predictions or decisions without being explicitly programmed for every task. Learning AI is used in many applications, including recommendation engines, language translation, and autonomous vehicles. As technology advances, Learning AI continues to play a crucial role in automating complex tasks and enhancing decision-making processes.

What are the key skills and qualifications needed to thrive as a learning AI engineer?

To thrive as a Learning AI Engineer, you need a solid background in computer science, mathematics, and machine learning, often supported by a relevant degree or certification. Familiarity with programming languages like Python, machine learning libraries (such as TensorFlow or PyTorch), and cloud computing platforms is typically required. Strong problem-solving skills, adaptability, and effective communication set outstanding professionals apart in this field. These skills are crucial for building, deploying, and refining AI models that solve real-world problems efficiently and ethically.

How do learning AI professionals typically collaborate with subject matter experts to develop effective training solutions?

Learning AI professionals frequently work alongside subject matter experts (SMEs) to ensure that AI-driven training tools and content are accurate, relevant, and engaging. This collaboration often involves regular meetings to gather domain-specific knowledge, iterative review of training modules, and feedback sessions to fine-tune AI models for optimal learning outcomes. Clear communication and a strong partnership with SMEs are essential, as they help bridge technical AI capabilities with real-world educational needs, resulting in more impactful and user-friendly learning solutions.

What is the difference between Learning Ai vs Data Scientist?

AspectLearning AiData Scientist
Required CredentialsTypically a degree in Computer Science, AI, or related fields; certifications in AI/MLDegree in Computer Science, Statistics, or related fields; certifications in data analysis or ML
Work EnvironmentTech companies, AI startups, research labs focusing on AI developmentBusiness environments, analyzing data to inform decisions across industries
Employer & Industry UsagePrimarily in AI development, research, and product creationAcross finance, healthcare, marketing, and other sectors for data analysis

Learning Ai focuses on developing algorithms and models that enable machines to learn and improve autonomously, often involving deep learning and neural networks. Data Scientists analyze and interpret complex data to help organizations make informed decisions. While both roles require knowledge of machine learning, Learning Ai is more centered on creating AI systems, whereas Data Scientists focus on extracting insights from data.

How do I start a career in learning ai?

To start a career in learning AI, develop a strong foundation in mathematics, programming (especially Python), and machine learning concepts. Gaining hands-on experience through projects, online courses, and certifications such as those from Coursera or edX can help build skills and demonstrate expertise to employers.

Is learning AI a good career path?

Learning AI can be a strong career choice due to high demand for skills in machine learning, data analysis, and programming languages like Python. Careers in AI often require continuous learning, strong problem-solving skills, and familiarity with tools such as TensorFlow or PyTorch. The field offers opportunities across industries including technology, healthcare, finance, and automotive sectors.

What are popular job titles related to Learning Ai jobs in Renton, WA?

For Learning Ai jobs in Renton, WA, the most frequently searched job titles are:

What job categories do people searching Learning Ai jobs in Renton, WA look for?

The top searched job categories for Learning Ai jobs in Renton, WA are:

What cities near Renton, WA are hiring for Learning Ai jobs?

Cities near Renton, WA with the most Learning Ai job openings:

Learning Ai jobs near you

Machine Learning Engineer - Remote

Seattle, WA • Remote

YO AI Labs
See more jobs at YO AI Labsexternal

$80 - $120/hr

Full-time

Posted 18 days ago

Job description

Senior Software Engineer

Job Type: Contractor (~15 hours/week)
Location: Remote

Job Summary

We are seeking experienced Senior Software Engineers to support an AI training project by creating reinforcement learning environments that evaluate AI models on complex software engineering tasks using Model Context Protocol (MCP) tools.

You will design reproducible environments, deterministic verification, and reference solutions for tasks such as bug fixing, feature implementation, codebase refactoring, and performance optimization. No prior AI experience is required.

Key Responsibilities
  • Create reinforcement learning environments for software engineering tasks.
  • Design tasks involving bug fixing, feature development, refactoring, and performance optimization.
  • Build deterministic verification systems and golden reference solutions.
  • Evaluate AI agents' ability to reason through complex codebases and use MCP tools effectively.
  • Develop realistic, reproducible software engineering scenarios.
  • Ensure tasks accurately measure coding ability, problem-solving, and tool usage.
  • Document solutions and provide clear technical feedback.
Required Skills
  • Strong proficiency in Python 3, Java, Rust, C++, or TypeScript.
  • Strong understanding of algorithms and data structures.
  • Experience with bug fixing and debugging complex software issues.
  • Proven experience in feature implementation and codebase refactoring.
  • Strong knowledge of performance optimization and tuning.
  • Excellent written and verbal communication.
  • Strong attention to detail.
Preferred Qualifications
  • Experience working with large-scale or distributed codebases.
  • Familiarity with AI/ML systems is a plus but not required.
  • Experience with rigorous code reviews and software engineering best practices.
  • Experience working effectively in remote or cross-functional teams.
Hiring Process
  1. Submit an application and screening questions.
  2. Complete an AI interview (~30 minutes).
  3. Complete a technical assessment, if required.
  4. Hiring Manager review.
Compensation

Compensation is output-based, with payment provided per task that meets project specifications. Minimum weekly submission requirements may apply.

Availability

Selected experts should be prepared to begin their first tasks within 24–48 hours of completing onboarding.