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Remote Retrieval Augmented Generation Jobs in Oregon

Cresta

Senior Machine Learning Engineer

OR · On-site +1

$205K - $270K/yr

Architect and scale LLM and retrieval-augmented generation pipelines that ground models in ... Remote work setup budget to help you create a productive home office * Monthly wellness and ...

Corvel

Data Scientist II

Retrieval-Augmented Generation (RAG) * Feature engineering and model evaluation techniques ... Remote

Tebra

Senior AI Automation Engineer

OR · On-site +1

$103K - $136K/yr

Own the Retrieval-Augmented Generation (RAG) lifecycle end-to-end, including ingestion, chunking ... Remote

LTS

Senior Applied AI Engineer

OR · On-site +1

$122K - $161K/yr

United States - Remote Clearance: Ability to obtain and maintain a Public Trust LTS is seeking a ... Continuously refine Retrieval-Augmented Generation (RAG) pipelines, retrieval strategies ...

LTS

Lead AI Architect/Strategist

OR · On-site +1

United States - Remote Clearance: Ability to obtain and maintain a Public Trust LTS is seeking a ... Retrieval-Augmented Generation (RAG), intelligent agents, and advanced analytics solutions. The ...

Cresta

Staff Machine Learning Engineer

OR · On-site +1

Architect and scale LLM and retrieval-augmented generation pipelines that ground models in ... Remote work setup budget to help you create a productive home office * Monthly wellness and ...

Delaware Nation Industries

AI Developer/Engineer

OR · On-site +1

This is a fully-remote opportunity. The AI Developer/Engineer designs, develops, integrates, and ... processing, retrieval-augmented generation, chatbots, document processing, classification ...

New

EM Key Solutions Inc

AI Engineer

OR · On-site +1

AI Engineer Remote, USA; potential for minimal ad hoc travel EMKS is seeking an AI Engineer to ... Build AI Copilots, AI Agents, and Retrieval-Augmented Generation (RAG) solutions to improve ...

EM Key Solutions Inc

Temporary AI Engineer

OR · On-site +1

AI Engineer Temporary Assignment (through 2/13/2027) Remote, USA; potential for minimal ad hoc ... Build AI Copilots, AI Agents, and Retrieval-Augmented Generation (RAG) solutions to improve ...

LTS

AI Platform and Harness Engineer

OR · On-site +1

This role is responsible for building the AI platform and reusable "AI harnesses" that enable Large Language Models (LLMs), AI agents, Retrieval-Augmented Generation (RAG), and Generative AI ...

Obsidian Security

Senior Support Engineer

OR · On-site +1

Global Services & Delivery Location: [Remote / Hybrid - specify] Reports to: Head of Customer ... Experience with LLM and agent frameworks, retrieval-augmented generation, or workflow automation.

Yubico Inc.

Sr. Director, Product Marketing

OR · On-site +1

A strategic understanding of how Large Language Models (LLMs), vector databases, and Retrieval-Augmented Generation (RAG) systems crawl, parse, and recommend technical enterprise software and ...

Grafana Labs

Staff AI Engineer | US | Remote

OR · On-site +1

This is a remote opportunity and we are looking for candidates from the U.S. The Opportunity ... Architect data flows for retrieval-augmented generation (RAG), connecting LLMs to internal ...

LTS

Senior Agentic AI Software Engineer

OR · On-site +1

$122K - $161K/yr

United States - Remote Clearance: Ability to obtain and maintain a Public Trust LTS is seeking a ... Design and optimize Retrieval-Augmented Generation (RAG) pipelines including document ingestion ...

LTS

Agentic AI Security Engineer

OR · On-site +1

United States - Remote Clearance: Ability to obtain and maintain a Public Trust LTS is seeking a ... Secure Retrieval-Augmented Generation (RAG) pipelines, embeddings, vector databases, and enterprise ...

Hitachi

Data Scientist I or II (MAD-BS-OR)

Hillsboro, OR · On-site +1

$121K - $167K/yr

Hybrid (+50% Remote) - Remote 60% / Onsite 40% EXPECTED PAY RANGE: Data Scientist I: $99,608 - $136 ... Retrieval-Augmented Generation (RAG) * Structured outputs and validation pipelines * Partner with ...

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Remote Retrieval Augmented Generation information

What skills and qualifications are needed to thrive as a remote retrieval augmented generation engineer?

To thrive as a Remote Retrieval Augmented Generation (RAG) Engineer, you need a strong background in machine learning, natural language processing, and information retrieval, often backed by a degree in computer science or a related field. Familiarity with tools and frameworks like PyTorch, TensorFlow, Hugging Face Transformers, and experience with retrieval systems such as Elasticsearch or FAISS are typically required. Problem-solving, effective communication, and adaptability are important soft skills for collaborating remotely and iterating on rapidly evolving AI solutions. These skills ensure the engineer can design, deploy, and optimize robust RAG systems that effectively combine retrieval and generation for high-quality AI outputs.

What is the difference between Remote Retrieval Augmented Generation vs Remote Data Scientist?

AspectRemote Retrieval Augmented GenerationRemote Data Scientist
CredentialsAI/ML knowledge, programming skillsStatistics, programming, domain expertise
Work EnvironmentAI development, NLP projectsData analysis, model building
Industry UsageAI, NLP, machine learningTech, finance, healthcare
Search & ComparisonOften compared for AI roles involving language modelsCompared for data analysis roles

Remote Retrieval Augmented Generation focuses on developing AI models that combine retrieval techniques with language generation, requiring expertise in AI, NLP, and programming. Remote Data Scientists analyze data, build models, and interpret results, often with statistical and domain knowledge. While both roles may work remotely and involve data handling, Retrieval Augmented Generation emphasizes AI model development, whereas Data Scientists focus on data analysis and insights.

What are common challenges faced by professionals working in remote retrieval augmented generation roles, and how can they be addressed?

Professionals in Remote Retrieval Augmented Generation (RAG) roles often encounter challenges related to integrating diverse data sources, ensuring low latency in information retrieval, and maintaining the quality and relevance of augmented outputs. Coordinating effectively with distributed teams and adapting to rapidly evolving AI technologies are also common hurdles. To address these, staying current with best practices in data engineering, leveraging robust APIs, and participating in regular team check-ins can help ensure smooth collaboration and system performance.

What is remote retrieval augmented generation?

Remote Retrieval Augmented Generation (RAG) is an advanced AI technique that combines large language models with external information sources. In a remote RAG setup, the model retrieves relevant data from remote databases or APIs during the generation process, enhancing its responses with up-to-date or domain-specific knowledge. This approach is widely used in applications that require accurate, context-aware answers, such as chatbots, search engines, and virtual assistants. By leveraging remote retrieval, RAG systems can access a broader range of information without needing to store all data locally.

What are the most commonly searched types of Retrieval Augmented Generation jobs in Oregon?

The most popular types of Retrieval Augmented Generation jobs in Oregon are:

What are popular job titles related to Remote Retrieval Augmented Generation jobs in Oregon?

For Remote Retrieval Augmented Generation jobs in Oregon, the most frequently searched job titles are:

What job categories do people searching Remote Retrieval Augmented Generation jobs in Oregon look for?

The top searched job categories for Remote Retrieval Augmented Generation jobs in Oregon are:

What cities in Oregon are hiring for Remote Retrieval Augmented Generation jobs?

Cities in Oregon with the most Remote Retrieval Augmented Generation job openings:

Remote Retrieval Augmented Generation jobs near you
Infographic showing various Remote Retrieval Augmented Generation job openings in Oregon as of August 2026, with employment types broken down into 68% Full Time, 28% Part Time, 3% Contract, and 1% Nights. Highlights an 67% Physical, 2% Hybrid, and 31% Remote job distribution.

Senior Machine Learning Engineer

Cresta

OR • On-site, Remote

$205K - $270K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 13 days ago

Job description

About the role:

Machine Learning Engineers at Cresta work across several high-impact AI initiatives. Final team placement is determined based on experience, strengths, and business needs.

Current focus areas include:

  • Agentic Assist: Lead and build next-generation agentic AI systems that augment contact center agents in real time. This track requires strong pre-LLM ML foundations, deep expertise in LLMs and modern prompting techniques, a rapid prototyping mindset, and a proven ability to translate cutting-edge research into scalable, production-grade systems.
  • Agent & System Quality: Design evaluation frameworks and improve the reliability, robustness, and performance of LLM-powered agents. This includes diagnosing and mitigating failure modes such as hallucinations, retrieval errors, tool misuse, context drift, prompt brittleness, and multi-step reasoning breakdowns, while defining measurable quality metrics (e.g., accuracy, faithfulness, task completion, latency, and cost) for complex, non-deterministic systems.
  • Insights: Architect and scale LLM and retrieval-augmented generation pipelines that ground models in enterprise data. This track focuses on building high-performance ML systems that process complex data, extract structured insights, and deliver real-time, actionable intelligence at scale.

Responsibilities:

  • Lead the design and development of Cresta's next-generation AI Agents and Agentic Assist systems, defining system architecture and core modeling approaches.
  • Architect intelligent, multi-step agent workflows that combine real-time guidance, knowledge retrieval, reasoning, summarization, and automated actions into cohesive production systems.
  • Design, deploy, and optimize LLM-powered systems, including Retrieval-Augmented Generation (RAG) pipelines, multi-agent orchestration, and domain-adapted models.
  • Improve reasoning, planning, and tool-use capabilities in real-world AI applications.
  • Develop evaluation strategies for complex, non-deterministic systems, including offline benchmarking, online experimentation, and LLM-as-a-judge methodologies.
  • Diagnose and mitigate real-world failure modes such as hallucinations, retrieval errors, tool misuse, prompt brittleness, and multi-step reasoning breakdowns.
  • Define and measure quality metrics (e.g., accuracy, faithfulness, task completion, latency, cost, robustness) to improve system reliability and performance.
  • Optimize AI systems for scalability, latency, security, and cost efficiency in production environments.
  • Collaborate cross-functionally with product, frontend, and backend teams to integrate AI capabilities seamlessly into Cresta's platform.
  • Mentor engineers, contribute to technical strategy, and help shape the roadmap for Cresta's AI systems.

Qualifications We Value:

  • Bachelor's degree in Computer Science, Mathematics, or a related field; Master's or Ph.D. preferred.
  • 5-8+ years of industry experience building and deploying machine learning systems in production, including significant experience working with LLMs.
  • Strong expertise in NLP, Generative AI, transformer architectures, embeddings, and retrieval systems.
  • Proven experience designing and deploying Retrieval-Augmented Generation (RAG) systems in enterprise environments.
  • Experience building and evaluating complex agentic or multi-step LLM workflows.
  • Strong knowledge of modern ML frameworks and tools (e.g., PyTorch, TensorFlow, Hugging Face) and distributed/cloud-based infrastructure.
  • Demonstrated ability to optimize real-time ML systems for performance, scalability, and reliability.
  • Strong technical leadership skills, with the ability to influence cross-functional decisions and raise the engineering bar.

Perks & Benefits:

We offer a comprehensive and people-first benefits package to support you at work and in life:

  • Comprehensive medical, dental, and vision coverage with plans to fit you and your family
  • Flexible PTO to take the time you need, when you need it
  • Paid parental leave for all new parents welcoming a new child
  • Retirement savings plan to help you plan for the future
  • Remote work setup budget to help you create a productive home office
  • Monthly wellness and communication stipend to keep you connected and balanced
  • In-office meal program and commuter benefits provided for onsite employees

Compensation at Cresta: 

Cresta's approach to compensation is simple: recognize impact, reward excellence, and invest in our people. We offer competitive, location-based pay that reflects the market and what each individual brings to the table.

The posted base salary range represents what we expect to pay for this role in a given location. Final offers are shaped by factors like experience, skills, education, and geography. In addition to base pay, total compensation includes equity and a comprehensive benefits package for you and your family.

Salary Range: $205,000-$270,000 + Offers Equity

We have noticed a rise in recruiting impersonations across the industry, where scammers attempt to access candidates' personal and financial information through fake interviews and offers. All Cresta recruiting email communications will always come from the @cresta.ai domain. Any outreach claiming to be from Cresta via other sources should be ignored.  If you are uncertain whether you have been contacted by an official Cresta employee, reach out to recruiting@cresta.ai 

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