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Remote Python Llm Jobs in Minneapolis, MN (NOW HIRING)

Kobie Marketing

AI Engineer

Minneapolis, MN · Remote

Join a National Top Workplace Named a Top Workplace in the USA and Top Remote Workplace, Kobie is ... Build agent harnesses in Python using LangChain and LangGraph, including tool-calling, structured ...

Kobie Marketing

AI Engineer

Minneapolis, MN · Remote

Join a National Top Workplace Named a Top Workplace in the USA and Top Remote Workplace, Kobie is ... Build agent harnesses in Python using LangChain and LangGraph, including tool-calling, structured ...

UnitedHealth Group

Data Scientist - Remote

Minnetonka, MN · On-site +1

$112K - $193K/yr

... experience with Python, Scala, SQL * 3+ years of Databricks, Spark * 2+ years of experience with LLM & GenAI Skills: * Creating custom embedding models * Building RAG pipelines * Vector DBs ...

A.C. Coy

Cloud Security Engineer/Architect (Remote)

Eagan, MN · Remote

$66.75 - $88.75/hr

... securing LLM-integrated applications against emerging attack vectors. * Automated Guardrails ... Proficiency in Python, Go, or Bash to build custom security automations and integrate with SOAR ...

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All JobsPython Llm JobsRemote Python Llm JobsRemote Python Llm Jobs in Minneapolis, MN

Remote Python Llm information

See Minneapolis, MN salary details

$13

$61

$90

How much do remote python llm jobs pay per hour?

As of Aug 3, 2026, the average hourly pay for remote python llm in Minneapolis, MN is $61.19, according to ZipRecruiter salary data. Most workers in this role earn between $50.43 and $69.52 per hour, depending on experience, location, and employer.

What remote jobs can you get with Python?

Remote Python jobs include roles such as software developer, data analyst, machine learning engineer, and automation engineer. These positions often require proficiency in Python programming, familiarity with frameworks like Django or Flask, and experience with cloud platforms or version control tools. Many of these jobs offer flexible schedules and can be performed from any location with internet access.

Will AI replace Python devs?

Remote Python developers are unlikely to be fully replaced by AI, as their role involves complex problem-solving, coding, and adapting to new requirements that AI tools currently cannot fully replicate. AI can assist by automating repetitive tasks and improving productivity, but human oversight and expertise remain essential for software development. Staying updated with new tools and skills can help Python developers remain valuable in an evolving tech environment.

What is a Remote Python LLM job?

A Remote Python LLM job typically involves working with large language models (LLMs) like GPT or similar AI technologies using the Python programming language, while operating remotely. Professionals in this role develop, fine-tune, and deploy machine learning models, especially those focused on natural language processing (NLP) tasks. Responsibilities may include building Python applications that integrate with LLMs, data preprocessing, and collaborating with teams across different locations. The remote aspect allows for flexible work arrangements and access to global opportunities.

What are some common collaboration methods used by Remote Python LLM engineers when working with cross-functional teams?

Remote Python LLM engineers frequently collaborate with data scientists, product managers, and other developers through virtual meetings, code reviews, and shared documentation platforms. Tools like Slack, GitHub, and Jira are often used to ensure smooth communication and project tracking, despite working across different time zones. Regular stand-ups and sprint planning sessions help align objectives and keep everyone updated on progress. Proactive communication and clear documentation are key to overcoming the challenges of remote, distributed teamwork in this role.

Is Python used in LLM?

Yes, Python is widely used in developing large language models (LLMs) and is a key skill for remote Python LLM roles. It provides extensive libraries and frameworks such as TensorFlow and PyTorch that facilitate model training, fine-tuning, and deployment.

What are the key skills and qualifications needed to thrive as a Remote Python LLM Engineer, and why are they important?

To thrive as a Remote Python LLM Engineer, you need strong proficiency in Python programming, experience with large language models (LLMs), and a degree in computer science or a related field. Familiarity with machine learning frameworks (such as TensorFlow or PyTorch), cloud platforms, and version control systems like Git is typically required. Excellent problem-solving abilities, self-motivation, and effective communication are crucial soft skills for remote collaboration and troubleshooting. These skills ensure you can develop, deploy, and maintain advanced language models efficiently while working independently in distributed teams.

Which LLM is good for Python coding?

For a Remote Python Llm role, models like OpenAI's GPT-4 and GPT-3.4 are widely used for Python coding due to their strong language understanding and code generation capabilities. Additionally, open-source models such as Meta's Llama 2 and EleutherAI's GPT-NeoX can be fine-tuned for specific coding tasks, making them suitable options for development environments requiring customization. Proficiency in integrating these models with APIs and understanding their limitations is essential for effective Python coding assistance.
What are popular job titles related to Remote Python Llm jobs in Minneapolis, MN? For Remote Python Llm jobs in Minneapolis, MN, the most frequently searched job titles are:
What job categories do people searching Remote Python Llm jobs in Minneapolis, MN look for? The top searched job categories for Remote Python Llm jobs in Minneapolis, MN are:
What cities near Minneapolis, MN are hiring for Remote Python Llm jobs? Cities near Minneapolis, MN with the most Remote Python Llm job openings:
Remote Python Llm jobs near you
Infographic showing various Remote Python Llm job openings in Minneapolis, MN as of July 2026, with employment types broken down into 58% Full Time, and 42% Contract. Highlights an 100% Remote job distribution, with an average salary of $127,273 per year, or $61.2 per hour.

Senior AI Engineer - Agentic Systems & Data Pipelines

Collaboration.Ai

Minneapolis, MN • Remote

$108K - $147K/yr

Full-time

Posted 5 days ago

Job description

Who We Are

Collaboration.Ai is a mission-focused, AI-powered software and services company based in Minnesota, with employees, partners, and customers around the world. We unite people, technology, and purpose to accelerate breakthroughs that transform industries, empower communities, and create a more sustainable future. We collaborate with organizations across the defense ecosystem, helping them navigate complex challenges and drive transformative change.

Our Products

NetworkOS — NetworkOS is an AI-powered platform that aligns people, purpose, ideas, and expertise in real-time, generating actionable insights to propel movements forward.

CrowdVector — CrowdVector is an integrated solution marketplace and innovation management platform that rapidly uncovers new ideas and advances breakthroughs to fuel movements.

To learn more about us, visit collaboration.ai.

About the Role

You'll build the agentic systems and data pipelines behind NetworkOS's AI capabilities: production agent workflows built on industry-leading agent SDKs and harnesses, MCP servers, and Agent Skills standards; the eval and observability layer that keeps LLM quality measurable; and the ingestion pipelines that turn messy, diverse data sources into queryable knowledge.

This is an execution seat, not an ivory tower. You'll commit code every week, ship agents as product capability rather than demos, and help shape a roadmap that's heading deep into graph + agents territory — for customers in defense, healthcare, and regulated enterprise.

Agents in production. Pipelines that hold. Evals that keep everyone honest.
This opportunity is remote with a preference for candidates in the Twin Cities area (Minneapolis, Saint Paul); however all candidates are encouraged to apply!

What You'll Do
  • Ship production agent systems — design, build, and operate agentic workflows (agent SDKs, MCP servers, Agent Skills standards) powering AI-driven matching, analysis, and data intelligence
  • Operationalize LLM quality — build the eval and observability layer with Langfuse, golden datasets, LLM-as-judge patterns, and FinOps-style tracking so every workflow has measurable quality, cost, and latency
  • Engineer data pipelines — robust ingestion of documents, structured data, and external sources into searchable knowledge bases with quality validation, deduplication, and incremental updates
  • Own retrieval quality — hybrid search combining vector, keyword, and metadata retrieval, continuously improved through reranking, query expansion, and contextual compression
  • Accelerate with AI — build custom MCP tools and Agent Skills that make the whole engineering team measurably faster
  • Execute alongside the team — pair with full-stack engineers on AI integration points, contribute to incident response for AI services, and keep your hands in the code
Our Tech Stack
  • Languages: Python (primary); Kotlin (core platform language at CAI); TypeScript/Node.js and other modern languages (secondary)
  • AI/ML: FastAPI, Pydantic; multi-provider LLM SDKs (Anthropic, OpenAI, and others)
  • Agentic Tooling: Claude Code/Codex/etc.; industry-leading agent SDKs and harnesses; MCP servers; Agent Skills standards
  • LLM Operations: Langfuse + evals (golden datasets, LLM-as-judge); in-house FinOps tracking (token usage, latency, cost); multi-provider orchestration including AWS Bedrock
  • Search & Retrieval: Vector databases, OpenSearch, embedding models
  • Data: PostgreSQL, Amazon S3; streaming pipelines (Kafka/Kinesis) where needed
  • Infrastructure: Docker, Kubernetes (AWS EKS); DataDog + OpenTelemetry observability
What We're Looking For

Must Haves

  • 7+ years of professional software engineering experience, with 3+ years focused on AI/ML or data engineering
  • Production agentic/LLM application experience — built and operated systems around LLM APIs (Anthropic, OpenAI) serving real users: agents, tool-use, or orchestrated LLM workflows
  • Data engineering background — robust, scalable pipelines for AI/ML workloads
  • LLM operations experience — evals and observability for production LLM systems (quality, cost, latency)
  • Production retrieval experience — vector databases and/or search engines (OpenSearch, Elasticsearch)
  • Modern Python stack proficiency — FastAPI, Pydantic, async/await, modern dependency management
  • AI-native workflows — demonstrated ability to leverage Claude Code/Codex or similar agentic coding tools to accelerate development
  • Experience with Docker, Kubernetes, and AWS
  • US citizenship required (DoD contracting — IL4/IL5 environments — and FedRAMP compliance)
Nice-to-Haves
  • Deep agentic ecosystem experience — Agent Skills standards, custom MCP servers, agent SDKs across major vendors
  • Advanced RAG expertise — GraphRAG, agentic RAG, contextual retrieval, reranking strategies
  • Graph data experience — knowledge graphs, graph databases, or graph-based retrieval
  • Model selection & rightsizing — matching models to domain-specific use cases across quality, cost, and latency tradeoffs
  • Streaming data experience (Kafka, Kinesis) for real-time knowledge base updates
  • Research background, open-source contributions, or an advanced degree in ML/IR/NLP
Why Join Collaboration AI?

Real AI engineering, not a wrapper shop. Production agents, hybrid retrieval, continuous evals, and a roadmap heading into graph + agents — with the autonomy to shape how it's built.

AI-native by default. We build with AI, not just for AI. Agentic coding tools (Claude Code/Codex/etc.), agent SDKs and harnesses, MCP servers, and Agent Skills standards are how we work daily — you'll both use and build them.

Work that matters. Defense, healthcare, and regulated industries — SOC 2 and NIST compliance, FedRAMP readiness, and customers whose missions demand AI they can trust.

Small, senior team. Early-stage impact with your work visible from week one. You'll help set the bar for how AI engineering is done here.

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