ZipRecruiter

Log In

2

Remote Rag Jobs in Goodyear, AZ (NOW HIRING)

Mondo

Data Scientist

Phoenix, AZ · Remote

$65 - $75/hr

Remote (Candidate must reside in Pacific, Mountain, or Central time zone. Eastern time zone and ... Design and deploy end to end RAG solutions and autonomous AI agents in cloud and enterprise ...

Epiq

Lead AI Software Engineer

Phoenix, AZ · Remote

Experience with MCP servers, agentic frameworks, and Retrieval-Augmented Generation (RAG). * Strong ... LI-Remote The Compensation range for this role is 120,000 to 170,000 USD annually and may be ...

All JobsRag JobsRemote Rag JobsRemote Rag Jobs in Goodyear, AZ

Remote Rag information

See Goodyear, AZ salary details

$16

$21

$23

How much do remote rag jobs pay per hour?

As of Aug 18, 2026, the average hourly pay for remote rag in Goodyear, AZ is $21.01, according to ZipRecruiter salary data. Most workers in this role earn between $17.60 and $22.31 per hour, depending on experience, location, and employer.

What is a Remote RAG?

A Remote RAG specialist is a professional who works with Retrieval-Augmented Generation (RAG) systems, typically in the field of artificial intelligence and machine learning. RAG combines traditional information retrieval techniques with generative models like large language models to provide more accurate and contextually relevant answers to user queries. Remote RAG specialists often build, fine-tune, and maintain these systems while working from a remote location. They may also work on integrating RAG models into applications, improving retrieval accuracy, and customizing outputs based on user needs.

What are the key skills and qualifications needed to thrive as a Remote RAG?

I'm sorry, but 'Remote Rag' does not appear to be a recognized professional occupation. Please provide a valid job title.

What are some common challenges faced by professionals working in a remote RAG role?

Professionals in remote RAG roles often encounter challenges related to cross-functional collaboration and maintaining clear communication, especially when working across different time zones. Ensuring alignment on ethical AI standards and compliance requirements can be complex, as it typically involves coordinating with data scientists, legal teams, and business stakeholders. Staying current with evolving regulatory frameworks and best practices in AI governance is also essential, demanding continuous learning and adaptability. Building trust and rapport within a remote team can require extra effort, but leveraging digital collaboration tools and regular check-ins can help mitigate these challenges.

What job categories do people searching Remote Rag jobs in Goodyear, AZ look for?

The top searched job categories for Remote Rag jobs in Goodyear, AZ are:

What cities near Goodyear, AZ are hiring for Remote Rag jobs?

Cities near Goodyear, AZ with the most Remote Rag job openings:

Remote Rag jobs near you

Senior AI Engineer / Data Scientist

Koantek

Chandler, AZ • Remote

Contractor

Re-posted 26 days ago

Job description

Senior AI Engineer / Data Scientist (Consulting) Location: United States (Remote) Employment Type: Full-Time / Contract Experience Level: Senior About the Role: We are seeking an experienced, highly technical Senior AI Engineer / Data Scientist to join our customer-facing consulting team. This remote role requires a unique blend of advanced Machine Learning (ML) expertise, deep knowledge of MLOps principles, and a proven track record in client-facing implementation. You will design, deploy, and maintain production-grade ML solutions, including advanced Generative AI and NLP models, for our diverse client base.

Key Responsibilities: * Technical Consulting: Lead end-to-end ML implementations directly with clients, translating business problems into robust technical solutions. * MLOps and Pipelines: Design, build, and maintain production-grade ML pipelines with a strong focus on CI/CD, automation, and scalability. * GenAI and NLP Deployment: Implement and optimize cutting-edge Generative AI applications (such as LLMs and RAG) in live production settings.

* Infrastructure and Data Scale: Manage underlying infrastructure using Docker, pipeline orchestrators, and distributed computing frameworks like Apache Spark. * Stakeholder Management: Clearly communicate technical findings, proposals, and project status to both technical and non-technical audiences. Required Qualifications: * 4+ years of professional experience developing, deploying, and maintaining ML models in a live production environment (Mandatory).

* 3+ years of experience in a customer-facing consulting or Solutions Architect role. * Strong expertise in the MLOps lifecycle (model versioning, testing, monitoring, and automated deployment). * Solid hands-on experience with containerization (Docker) and data pipeline orchestration.

* Proven track record of deploying Generative AI and NLP solutions for client applications. * Excellent verbal and written communication skills. Preferred Qualifications: * Hands-on experience with modern ML platform stacks, specifically Databricks MLOps Stacks.

* Deep knowledge of large-scale data processing and distributed machine learning techniques. * A strong commitment to continuous learning in emerging ML fields and GenAI application architectures.

Apply