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Python Llm Jobs in Minnesota (NOW HIRING)

Pwc

GenAI Python Systems Engineer-Manager

Minneapolis, MN

$99K - $232K/yr

... Python and SQL - Experience with Docker and containerized deployments - Skilled in AI techniques ... LLM optimization - Implementing data integration solutions using AWS, Azure, GCP - Utilizing AWS ...

Virtusa

Agentic AI Architect

Minneapolis, MN · On-site

Design robust AI/ML architectures for LLM-based systems, including prompt strategies, RAG, and evaluation frameworks. * Write and review production-quality Python code and establish testing, CI/CD ...

Mindlance

AI Software Engineer

Hopkins, MN

... LLM models for reasoning, generation, and decision-making capabilities Manage and optimize vector ... Python and Java (Spring Boot) Hands-on experience with LangChain, LangGraph, and Agentic AI ...

Virtusa

AI Fullstack Engineer

Minneapolis, MN · On-site

Skills:- Java/Python/.NET, Git, REST APIs, CI/CD basics, React; GH Copilot, Claude Code (or agentic ... LLM/agent runtimes, or data platforms via APIs. - Strong problem-solving skills and ability to ...

UnitedHealth Group

AI Engineer - AI/ML

Minnetonka, MN · Hybrid

$116.70K - $140.20K/yr

Build and optimize end-to-end pipelines using Python (Sci-kit Learn, Pandas, Flask, LangChain ... Apply best practices for LLM security, including output moderation, access control, and ...

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What is a Python LLM job?

A Python LLM job involves working with Large Language Models (LLMs) using Python to develop, fine-tune, and deploy AI models. Responsibilities may include data preprocessing, prompt engineering, model optimization, and integration with applications. Professionals in this role often work with frameworks like TensorFlow, PyTorch, or Hugging Face Transformers. They may also contribute to improving model efficiency, reducing bias, and ensuring ethical AI usage.

What are the key skills and qualifications needed to thrive in the Python Llm position, and why are they important?

To excel as a Python LLM (Large Language Model) Engineer, you need strong skills in Python programming, machine learning, and natural language processing, typically supported by a degree in computer science or a related field. Proficiency with libraries such as TensorFlow, PyTorch, Hugging Face Transformers, and experience with model deployment platforms are often essential, alongside certifications in AI or data science. Effective communication, problem-solving abilities, and collaboration are important soft skills for working in interdisciplinary teams and delivering results in dynamic environments. These skills ensure the development, fine-tuning, and deployment of advanced language models that meet both technical and business objectives.

What are some common challenges faced by Python LLM Engineers in their daily work?

Python LLM Engineers often encounter challenges related to optimizing model performance, managing large datasets, and adapting models to specific business needs. Working with large-scale language models requires balancing computational resource limitations with the need for high accuracy and efficiency. Collaboration with data scientists, product managers, and DevOps engineers is routine to ensure seamless model integration and deployment. Staying updated on the latest advancements in NLP and continuously improving models based on user feedback are also important aspects of the role.
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Python Llm jobs near you
Software Engineer - LLM Infrastructure

Software Engineer - LLM Infrastructure

Swoop Search

Minneapolis, MN • On-site

$180.60K - $214K/yr

Full-time

Posted 9 days ago

Job description

About Swoop:
Swoop Technologies has a mission to organize and make accessible the world's military and critical infrastructure. We are building a distributed operating system, SwoopOS, that decomposes the world's equipment into a distributed robotic embodiment upon which a new generation of distributed systems, autonomous systems, and agentic AI can be built and deployed using our SDK, Valhalla, and operated via our browser, Surf. Imagine the world's equipment - consisting of the electrical grid, communications architectures, manufacturing facilities, and militaries as a trapped supply of inputs possessing the potential to ensure Western military advantage, sovereign control of economically competitive manufacturing capacity, or the creation of a grid that fosters energy dominance. Swoop is liberating these trapped assets, allowing them to contribute to the world's future as a series of building blocks to be combined at the speed of software, limited by only the hard constraints of physics and the soft constraints of safety. That is what Swoop is building. Not in the data center or cloud or edge on-premise computing node. In the physical world. This is a hybrid position that requires someone based in Minneapolis/St. Paul OR Washington, DC who can work in-office 3+ days per week
Impact:
Swoop's operating system challenges many paradigms defining a scalable API. Management, security, and interoperability each will be re-imagined in how Swoop OS's expose interfaces to inputs and outputs within the stack. In this role, you will develop, maintain, and scale Swoop's self-hosted, custom-tuned LLM. A key objective is advancing how the model understands and represents complex system interactions, providing context-aware insights into system behavior, dependencies, and operational dynamics. You will enable users to ask natural, unconstrained questions about their infrastructure and systems, receiving precise, insight-driven responses. The ultimate goal is to accelerate decision making and drive greater autonomy across distributed infrastructure powered by Swoop OS.
What You'll Do:
  • Develop and maintain Swoop's LLM offering
  • Expand the capabilities of the LLM to interact with the system via tool calls
  • Expand the data searching capabilities of the LLM
  • Work hand-in-hand with frontend developers to build out new LLM features and improve existing ones
  • Monitor the resource usage of installations and make sure that the LLM offering is as efficient and fast as possible given the inference hardware available
  • Maintain and optimize inference engine architecture
  • Tune data storage configurations to optimize for scale and near real-time availability in a streaming architecture
  • Ensure our services have strong availability and service level agreements across our code base, especially as it pertains to the runtime of our Kubernetes cluster in production

You Should Have:
  • Bachelor's degree in Computer Science or related technical field, or equivalent technical experience
  • Firm understanding of scalable large language model infrastructure
  • Experience with low-level NVIDIA drivers and NVIDIA Kubernetes Container Toolkit
  • Familiarity with designing RAG information retrieval systems and time-series anomaly detection
  • Experience with PyTorch, training and fine-tuning Machine Learning models for resource-light environments
  • Experience with Kubernetes in a production environment
  • Proficient Python coding ability with good understanding of data structures and data models
  • Active US Security clearance or ability and willingness to be sponsored for a US Security clearance

Bonus if you have:
  • Experience with on premise or self-hosted AI
  • Experience with numerous GPUs and understanding of performance characteristics
  • Experience standing up inference engines such as vLLM

Swoop Technologies is proud to be an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, age, national origin, disability, protected veteran status, gender identity or any other factor protected by applicable federal, state, or local laws.

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