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Llm Ml Rag Jobs in Minnesota (NOW HIRING)

Vizient

Senior Software Engineer

Minneapolis, MN

$102K - $179K/yr

Collaborate with AI/ML engineers to deploy and support machine learning models, LLM applications, RAG pipelines, and agentic AI solutions in production environments. * Leverage AI-assisted ...

Vizient, Inc.

Senior Software Engineer

Edina, MN · On-site

$102K - $179K/yr

Collaborate with AI/ML engineers to deploy and support machine learning models, LLM applications, RAG pipelines, and agentic AI solutions in production environments. * Leverage AI-assisted ...

Vizient

Senior Software Engineer

Minneapolis, MN · On-site

$102K - $179K/yr

Collaborate with AI/ML engineers to deploy and support machine learning models, LLM applications, RAG pipelines, and agentic AI solutions in production environments. * Leverage AI-assisted ...

Vizient, Inc.

Senior Software Engineer

Edina, MN · On-site

$102K - $179K/yr

Collaborate with AI/ML engineers to deploy and support machine learning models, LLM applications, RAG pipelines, and agentic AI solutions in production environments. * Leverage AI-assisted ...

FAVARH

AI Principal Engineer

Minneapolis, MN · On-site +1

... RAG) pipelines, and model-driven services. * Own technical direction for major AI platform ... Experience with AI/ML frameworks, large language model (LLM) technologies, and modern data ...

Deloitte

Google AI Architect

Minneapolis, MN

LLM and AI Integration: Integrate and fine-tune Large Language Models (LLMs) and other AI/ML models ... RAG with Vertex AI Search/Vector Search, prompt design, safety policies, observability). * Deep ...

Abotts Inc

Senior AI Engineer

Eden Prairie, MN · On-site

$120 - $160/hr

Architect and implement model orchestration, retrieval-augmented generation (RAG), evaluation, and ... Required Qualifications * 8+ years of professional software / ML engineering experience, with 2+ ...

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Llm Ml Rag information

What is an llm ml rag job?

LLM ML RAG jobs involve working with Large Language Models (LLMs), Machine Learning (ML), and Retrieval-Augmented Generation (RAG) systems. Professionals in these roles typically design, develop, and optimize AI systems that combine language models with retrieval techniques to improve accuracy, relevance, and factual grounding in generated outputs. These jobs often require expertise in natural language processing, deep learning, data engineering, and information retrieval. Key responsibilities might include integrating RAG pipelines, fine-tuning LLMs, and ensuring high-quality responses from AI applications.

What are some typical challenges faced when working on retrieval-augmented generation (RAG) systems in large language model (LLM) machine learning roles?

Professionals working on LLM ML RAG systems often encounter challenges such as ensuring the accuracy and relevancy of retrieved documents, managing latency for real-time queries, and seamlessly integrating retrieval mechanisms with generation models. Additionally, keeping up with evolving datasets and maintaining high-quality knowledge bases can be demanding. Collaboration with data engineers and domain experts is common to refine retrieval pipelines and optimize the end-to-end system.

What are the key skills and qualifications needed to thrive as an llm ml rag engineer, and why are they important?

To excel as an LLM ML RAG Engineer, you need a strong background in machine learning, natural language processing, and large language models, typically supported by a degree in computer science or a related field. Proficiency with tools and frameworks like Python, PyTorch/TensorFlow, Hugging Face Transformers, and vector databases (e.g., FAISS, Pinecone) is essential, along with experience in deploying and fine-tuning LLMs and integrating retrieval systems. Strong problem-solving skills, attention to detail, and the ability to collaborate with cross-functional teams distinguish top performers in this role. These skills ensure the effective development and deployment of advanced AI solutions that combine generative and retrieval capabilities for high-impact applications.

What is the difference between Llm Ml Rag vs Data Scientist?

AspectLlm Ml RagData Scientist
Required CredentialsMaster's or PhD in ML, AI, or related fields; certifications in ML frameworksDegree in Computer Science, Statistics, or related; certifications in data analysis or ML
Work EnvironmentResearch labs, AI development teams, tech companiesBusiness analytics, research, product development teams
Employer & Industry UsageTech firms, AI startups, research institutionsFinance, healthcare, tech, consulting firms
Common Search & ComparisonOften compared for ML specialization and research focusCompared for data analysis, modeling, and business insights

While both roles involve working with machine learning, Llm Ml Rag typically focuses on research and development of large language models, requiring advanced ML expertise. Data Scientists often work on analyzing data, building predictive models, and deriving insights for business decisions. The roles overlap in skills but differ in focus and application areas.

What are popular job titles related to Llm Ml Rag jobs in Minnesota?

For Llm Ml Rag jobs in Minnesota, the most frequently searched job titles are:

What job categories do people searching Llm Ml Rag jobs in Minnesota look for?

The top searched job categories for Llm Ml Rag jobs in Minnesota are:

What cities in Minnesota are hiring for Llm Ml Rag jobs?

Cities in Minnesota with the most Llm Ml Rag job openings:

Llm Ml Rag jobs near you

Senior Software Engineer

Vizient

Minneapolis, MN

$102K - $179K/yr

Full-time

Re-posted 23 days ago

Job description

When you're the best, we're the best. We instill an environment where employees feel engaged, satisfied and able to contribute their unique skills and talents while living and working as their authentic selves. We provide extensive opportunities for personal and professional development, building both employee competence and organizational capability to fuel exceptional performance through an inclusive environment both now and in the future.

Summary:

In this role, you will design, develop, and support scalable backend systems, cloud infrastructure, and data platform capabilities that power AI/ML products and healthcare analytics solutions. You will collaborate with AI/ML engineers, data scientists, product teams, and clients to deploy machine learning models, LLM applications, and intelligent automation solutions into production. You will leverage modern cloud technologies, infrastructure-as-code practices, and AI-assisted development tools to deliver secure, reliable, and maintainable software while contributing to engineering standards, operational excellence, and continuous innovation.

Responsibilities:

  • Design, develop, and maintain backend services, APIs, distributed systems, and platform components that support AI/ML applications and healthcare analytics solutions.
  • Build and support cloud infrastructure, containerized environments, CI/CD pipelines, and deployment workflows using infrastructure-as-code frameworks.
  • Develop data-intensive applications, data pipelines, and cloud-based data platforms that enable analytics, artificial intelligence, and machine learning initiatives.
  • Collaborate with AI/ML engineers to deploy and support machine learning models, LLM applications, RAG pipelines, and agentic AI solutions in production environments.
  • Leverage AI-assisted development tools to accelerate software delivery while ensuring code quality, security, maintainability, and reliability.
  • Validate, test, and optimize software solutions, including AI-generated code, to ensure performance, scalability, and production readiness.
  • Implement monitoring, logging, tracing, alerting, and operational support practices to improve system reliability and performance.
  • Apply engineering standards for testing, security, scalability, cost efficiency, and software development best practices.
  • Partner with product, data, platform, security, and business teams to deliver production-ready solutions and support technical design discussions.
  • Mentor team members through code reviews, technical collaboration, and knowledge sharing.

Qualifications:

  • Relevant degree preferred.
  • 5 or more years of relevant experience required.
  • Strong Python or Java development experience with expertise building production backend services, APIs, distributed systems, and cloud-based applications required.
  • Experience with AWS, Azure, GCP, or similar cloud platforms and infrastructure-as-code tools such as Pulumi or Terraform required.
  • Experience building data-intensive applications, data platforms, data pipelines, ETL/ELT processes, or modern data engineering solutions highly preferred.
  • Experience supporting machine learning systems, model serving, LLM applications, RAG workflows, agentic AI solutions, or related AI technologies highly preferred.
  • Experience with containerization, Kubernetes, CI/CD pipelines, infrastructure automation, and cloud deployment practices preferred.
  • Experience leveraging AI-assisted development tools and validating AI-generated code in production environments preferred.
  • Experience with Databricks, Snowflake, Azure AI Foundry, observability platforms, monitoring, logging, tracing, or production support practices preferred.
  • Experience working with healthcare data, healthcare technology platforms, or healthcare analytics solutions highly preferred.

Estimated Hiring Range:

At Vizient, we consider skills, experience, and organizational needs in our compensation approach. Geographic factors may adjust the range estimate and hires typically fall below the top range. Compensation decisions are tailored to individual circumstances. The current salary range for this role is $102,400.00 to $179,000.00.

This position is also incentive eligible.

Vizient has a comprehensive benefits plan! Please view our benefits here:

http://www.vizientinc.com/about-us/careers

Equal Opportunity Employer: Females/Minorities/Veterans/Individuals with Disabilities

The Company is committed to equal employment opportunity to all employees and applicants without regard to race, religion, color, gender identity, ethnicity, age, national origin, sexual orientation, disability status, veteran status or any other category protected by applicable law.

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