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Python Llm Jobs in Minnesota (NOW HIRING)

Blank Metal Inc

AI Engineer

Minneapolis, MN · On-site

$108K - $146K/yr

Deep hands-on experience with LLM APIs (OpenAI, Anthropic, etc.) and frameworks like LangChain * Full-Stack Skills : Strong development across frontend (React/modern frameworks), backend (Python ...

Kobie Marketing

AI Engineer

Minneapolis, MN · Remote

... clients an LLM-native way to work with complex loyalty logic. We're looking for a hands-on AI ... Build agent harnesses in Python using LangChain and LangGraph, including tool-calling, structured ...

Accenture

AI & HPC Infrastructure Engineer

Minneapolis, MN · On-site

$112K - $147K/yr

... Python and modern API patterns such as REST, OpenAPI, JSON/YAML schemas, webhooks, and event-driven integrations. * Experience designing and implementing agentic AI infrastructure, including LLM ...

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Python Llm information

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.

What are the most commonly searched types of Python Llm jobs in Minnesota? The most popular types of Python Llm jobs in Minnesota are:
What are popular job titles related to Python Llm jobs in Minnesota? For Python Llm jobs in Minnesota, the most frequently searched job titles are:
What job categories do people searching Python Llm jobs in Minnesota look for? The top searched job categories for Python Llm jobs in Minnesota are:
What cities in Minnesota are hiring for Python Llm jobs? Cities in Minnesota with the most Python Llm job openings:
Python Llm jobs near you

AI Evaluation & Benchmarking Engineer IRC299413

Hitachi Rail

Minneapolis, MN • On-site

Full-time

Posted 8 days ago

Job description

Job Summary:
GlobalLogic, a Hitachi Group Company, is a trusted digital engineering partner to the world's largest and most forward-thinking companies. They are seeking an AI Evaluation & Benchmarking Engineer to support the productionization of an AI evaluation platform, focusing on reinforcement learning and LLM-based agents in video game environments.
Responsibilities:
• Develop, adapt, and integrate reinforcement learning algorithms and baseline approaches into the shared evaluation platform.
• Integrate LLM-based agents and/or evaluators for solving, interacting with, and benchmarking game environments.
• Integrate external or off-the-shelf algorithms into the platform using defined execution and ingestion workflows.
• Design and run benchmark experiments across games, environments, configurations, agents, and algorithm versions.
• Define evaluation strategies for comparing RL, LLM-based, hybrid, and baseline approaches.
• Define, extract, and validate meaningful performance metrics from logs, outputs, run results, and environment interactions.
• Build comparison logic, scoring approaches, rankings, verdicts, and performance summaries.
• Develop analytics and visualizations to evaluate algorithm performance across runs and environments.
• Act as a primary power user of the platform, running experiments and identifying gaps in tooling, APIs, metrics, workflows, logs, and user experience.
• Provide structured feedback to Platform and Full Stack engineers to improve execution, logging, evaluation, and reporting capabilities.
• Validate existing game environments and support development or validation of new game environments.
• Evaluate environment operability using baseline/reference frontier LLM models, harnesses, and agents.
• Collaborate with client technical teams and engineering resources within 3M-owned repositories, workflows, infrastructure, and security processes.
• Ensure all algorithms, experiments, notebooks/scripts, configuration, documentation, and outputs comply with 3M-defined standards and policies.
Qualifications:
Required:
• Hands-on reinforcement learning experience.
• Experience using LLMs for agents, evaluation, reasoning, automation, or benchmark workflows.
• Strong Python experience for ML, data workflows, experimentation, and analysis.
• Experience designing and running experiments with statistical and analytical rigor.
• Strong understanding of evaluation metrics, scoring frameworks, performance comparison, and benchmark design.
• Experience analyzing structured logs, run outputs, model/agent performance, and experiment results.
• Ability to work across APIs, logs, CLI/tools, data structures, and platform workflows.
• Strong communication skills to translate experiment findings into platform improvement requirements.
• Ability to work inside client-owned repositories, infrastructure, workflows, and security controls.
Preferred:
• Experience with game environments, simulation environments, Gym-like interfaces, RL environments, or agentic AI test harnesses.
• Experience benchmarking LLM agents, RL policies, autonomous agents, or hybrid AI systems.
• Experience with experiment tracking, run comparison tools, metrics dashboards, or evaluation pipelines.
• Experience with prompt engineering, agent orchestration, tool use, and LLM evaluation frameworks.
• Experience with data visualization and performance analytics.
• Experience working with externally developed algorithms, reproducible experiments, and version-controlled evaluation workflows.
Company:
Hitachi Rail is a provider of rail solutions across rolling stock, signalling services and turnkey. Founded in , the company is headquartered in London, GBR, with a team of 10001+ employees. The company is currently Late Stage.

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