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Python Llm Jobs in Saint Louis, MO (NOW HIRING)

Bespoke Labs

Machine Learning Engineer

Edwardsville, IL · On-site

... Python and deep learning proficiency (PyTorch preferred; familiar with training loops, optimizers, mixed precision) Hands-on experience with LLM post-training -- SFT, RLHF, PPO, DPO, or reward model ...

Parsons

Senior Agentic AI UI Devleoper

Saint Louis, MO

$148K - $266K/yr

Strong proficiency in Python for backend services, automation, AI integration, and tooling ... Experience with langchain or other LLM frameworks Security Clearance Requirement: An active Secret ...

Nestle

Expert Data Scientist

Saint Louis, MO

$130K - $188K/yr

... in Python/SQL for advanced analytics, data engineering, and model development * 2+ years of experience designing, fine-tuning, evaluating, and deploying LLM-based applications for various data ...

Keeley Construction

Snowflake Data Architect

Saint Louis, MO · Hybrid

$62 - $79.75/hr

Design and implement Snowflake Cortex capabilities, including AI SQL, LLM functions, document ... Experience implementing Snowflake Cortex, Snowpark (Python), AI SQL, and AI-driven analytics ...

Nestle

Data Scientist

Saint Louis, MO

$88K - $123K/yr

... Python and SQL * Design andmaintainreusable analytics workflows and automated pipelines for ... Familiarity with LLM orchestration frameworks (e.g.,LangChainor Semantic Kernel), prompt ...

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How much do python llm jobs pay per hour?

As of Aug 13, 2026, the average hourly pay for python llm in Saint Louis, MO is $56.99, according to ZipRecruiter salary data. Most workers in this role earn between $46.97 and $64.76 per hour, depending on experience, location, and employer.

What is a Python LLM?

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

Machine Learning Engineer

Bespoke Labs

Edwardsville, IL • On-site

Full-time

Re-posted 27 days ago

Job description

About Us

We are AI researchers and builders who understand how to curate data and RL environments that truly improve models. We curated OpenThoughts, one of the best open reasoning datasets, and have trained SOTA models such as Bespoke-MiniCheck and Bespoke-MiniChart.

We are embarked on a journey to build Environments that are entire digital worlds that can be used to push the frontier of agents.

What You'll Be Working On

You will work directly with our research team on RL environment and task creation for agent training. This means designing observation spaces, action spaces, reward signals, and success criteria for new environments — and building the infrastructure that makes world-scale RL training possible. This is a high-ownership role; you will be building novel systems, not maintaining legacy ones.

Must-Have Skills

3+ years of ML engineering experience — model training, fine-tuning, or post-training pipelines in research or production

Strong Python and deep learning proficiency (PyTorch preferred; familiar with training loops, optimizers, mixed precision)

Hands-on experience with LLM post-training — SFT, RLHF, PPO, DPO, or reward model training — and understanding of how training data quality affects model behavior

Familiarity with RL frameworks (Gymnasium, dm_env) and the ability to design or modify reward functions for agent training objectives

Experience running experiments at scale on cloud or HPC (AWS, GCP, SLURM, or Ray)

Solid understanding of evaluation methodology — held-out sets, benchmark design, avoiding train/eval contamination

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