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Python Llm Jobs in Lancaster, SC (NOW HIRING)

Hands on strong Python development, scripting, and APIs. * Infrastructure & cloud: infrastructure ... GitHub Copilot, Cursor AI, prompt engineering, LLM-based software development, and AI-assisted ...

Implement GraphRag in AI/ML products deployed to production to improve LLM response. * Design and ... Expert-level programming skills in Python/PySpark and Java. * Experience building user interfaces ...

New

... 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 ...

Does not need SQL, Python, or AI build experience at all. * Technical depth would come more from knowledge of AI platforms - cloud cost structures, compute costs, token costing, inference, LLM cost ...

AI Engineer

Fort Mill, SC · On-site

$75 - $85/hr

Implement GraphRag in AI/ML products deployed to production to improve LLM response. * Design and ... Expert-level programming skills in Python/PySpark and Java. * Experience building user interfaces ...

New

Implement GraphRag in AI/ML products deployed to production to improve LLM response. * Design and ... Expert-level programming skills in Python/PySpark and Java. * Experience building user interfaces ...

New

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Python Llm information

See Lancaster, SC salary details

$11

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How much do python llm jobs pay per hour?

As of Aug 20, 2026, the average hourly pay for python llm in Lancaster, SC is $50.00, according to ZipRecruiter salary data. Most workers in this role earn between $41.20 and $56.78 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.

What job categories do people searching Python Llm jobs in Lancaster, SC look for?

The top searched job categories for Python Llm jobs in Lancaster, SC are:

ML-Ops / Platform Engineer

Long Finch Technologies

Weddington, NC • On-site

$49.25 - $67.50/hr

Full-time

Posted yesterday

New


Job description

Must have skills: MLOps, AWS/Azure, Kubernetes, Docker, Python, Terraform, CI/CD, GenAI/LLM, RAG, Bedrock/Azure OpenAI, Vector DB, Observability Responsibilities:

·       Designed, deployed, and operated enterprise-grade MLOps/GenAI platforms across AWS and Azure, leveraging AWS Bedrock, SageMaker, Azure OpenAI, Azure AI Foundry, model serving, embeddings, RAG, vector databases, AI gateways, guardrails, and agentic frameworks.

·       Built and automated cloud-native ML infrastructure using Terraform, Kubernetes (EKS/AKS/OpenShift), Docker, GitHub Actions, Azure DevOps, Jenkins, GitOps, and ArgoCD, enabling scalable model deployment, CI/CD, versioning, and release management.

·       Implemented secure and highly available ML/AI platforms using AWS IAM, Azure IAM/RBAC, VPC/VNet, Key Vault, Secrets Manager, API Gateway, load balancers, ingress controllers, service mesh, autoscaling, and multi-account/subscription architectures.

·       Developed and operationalized ML/GenAI workloads using Python, REST APIs, microservices, MongoDB, PostgreSQL, Redis, and vector databases, implementing model evaluation, prompt engineering, state management, caching, and high-throughput inference capabilities.

·       Monitored, troubleshot, and optimized production ML/AI workloads using observability, logging, monitoring, SRE practices, performance tuning, resiliency, disaster recovery, and cost optimization, while collaborating with application, platform, infrastructure, and security teams.