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Freelance 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 enterprise data. This track focuses on building high-performance ML systems that process complex data ...

Smarsh

OR · On-site

$122K - $161K/yr

Design and optimize retrieval-augmented generation (RAG) pipelines, including handling long documents and retrieval quality * Contribute to knowledge graph-driven approaches to enhance search ...

Corvel

Data Scientist II

Support advanced AI use cases, including LLM-based solutions, retrieval-augmented generation (RAG), and hybrid modeling approaches where appropriate * Collaborate with engineering teams to integrate ...

RTI International

Help develop retrieval-augmented generation (RAG) pipelines and agent-based workflows. * Build and consume REST APIs and cloud-native services. * Write clean, maintainable, well-tested code using AI ...

Tebra

Senior AI Automation Engineer

OR · Remote

$103K - $136K/yr

Own the Retrieval-Augmented Generation (RAG) lifecycle end-to-end, including ingestion, chunking strategy, embeddings, vector storage, and reranking. * Implement data quality checks and architectural ...

LTS

Lead AI Architect/Strategist

OR · Remote

... Retrieval-Augmented Generation (RAG), intelligent agents, and advanced analytics solutions. The ideal candidate is a strategic technology leader with deep expertise in AI architecture, cloud ...

LTS

Senior Applied AI Engineer

OR · Remote

$122K - $161K/yr

Continuously refine Retrieval-Augmented Generation (RAG) pipelines, retrieval strategies, embeddings, reranking, and grounding techniques. * Improve AI response quality through experimentation ...

Cresta

OR · On-site

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 ...

LTS

OR · On-site

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 ...

Netflix

OR · On-site

You'll leverage large language models, agentic frameworks, and retrieval-augmented generation to solve real infrastructure and product problems, with a direct impact on how quickly and confidently ...

EM Key Solutions Inc

AI Engineer

OR · On-site +1

Build AI Copilots, AI Agents, and Retrieval-Augmented Generation (RAG) solutions to improve software engineering, testing, documentation, and operational workflows. * Develop intelligent automation ...

EM Key Solutions Inc

Temporary AI Engineer

OR · On-site +1

Build AI Copilots, AI Agents, and Retrieval-Augmented Generation (RAG) solutions to improve software engineering, testing, documentation, and operational workflows. * Develop intelligent automation ...

HealthEquity

Designing and developing AI/LLM-powered capabilities for internal business problems - including retrieval-augmented generation, orchestration, prompt and model integration - using Azure AI services ...

Yubico Inc.

OR

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 ...

Obsidian Security

Senior Support Engineer

OR · On-site +1

Experience with LLM and agent frameworks, retrieval-augmented generation, or workflow automation. * Familiarity with identity provider and SaaS administrative APIs, such as Microsoft Graph and Entra ...

Slalom Consulting

General Information

Portland, OR · On-site

$91K - $115K/yr

... Retrieval-Augmented Generation (RAG), Cache-Augmented Generation (CAG), prompt engineering, model routing, and how these choices impact cost, performance, scalability, and business value. * Ability ...

Defense Unicorns

OR · On-site

APIs, data processing pipelines, integration layers, Retrieval Augmented Generation (RAG), and context engineering patterns. * Deploy and operate systems in cloud, on-prem, and air-gapped ...

LTS

Senior Agentic AI Software Engineer

OR · On-site +1

$122K - $161K/yr

Design and optimize Retrieval-Augmented Generation (RAG) pipelines including document ingestion, embeddings, hybrid retrieval, reranking, semantic search, context engineering, and prompt ...

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Freelance Retrieval Augmented Generation information

What are the key skills and qualifications needed to thrive as a freelance retrieval augmented generation specialist?

To thrive as a Freelance Retrieval Augmented Generation (RAG) Specialist, you need expertise in natural language processing, information retrieval, and machine learning, typically supported by a degree in computer science or related fields. Proficiency with frameworks like Hugging Face Transformers, vector databases (e.g., FAISS, Pinecone), and cloud platforms is often required. Strong problem-solving, effective communication, and adaptability set standout professionals apart in this role. These skills ensure the development and fine-tuning of high-performance RAG systems that deliver accurate, contextually relevant results for clients.

What is a freelance retrieval augmented generation specialist?

A Freelance Retrieval Augmented Generation (RAG) specialist is an independent professional who designs, develops, and implements AI systems that combine retrieval-based methods with generative models. RAG specialists help organizations enhance their applications by integrating large language models (LLMs) with external data sources, allowing the AI to access and utilize up-to-date information beyond its training data. Their work involves tasks such as building pipelines for document indexing and retrieval, fine-tuning models, and optimizing the integration for accuracy and efficiency. Freelance RAG specialists typically work on a contract basis, offering flexibility and expertise for businesses that need advanced AI solutions.

How does a freelance retrieval augmented generation specialist typically collaborate with client teams during a project?

Freelance Retrieval Augmented Generation (RAG) specialists often work closely with client data scientists, engineers, and project managers to understand business requirements and integrate RAG systems into existing workflows. Communication is usually handled through regular virtual meetings, shared documentation, and sometimes real-time collaboration tools. Freelancers are expected to deliver modular, well-documented solutions and provide guidance on optimizing retrieval pipelines or fine-tuning models. This collaborative dynamic ensures that RAG implementations are aligned with client goals and technical standards, while also allowing freelancers to contribute innovative solutions based on their expertise.
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 Freelance Retrieval Augmented Generation jobs in Oregon? For Freelance Retrieval Augmented Generation jobs in Oregon, the most frequently searched job titles are:
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Freelance Retrieval Augmented Generation jobs near you

Senior Machine Learning Engineer

Cresta

OR • On-site, Remote

$205K - $270K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 7 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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