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Remote Python Llm Jobs in Chester, VA (NOW HIRING)

Axiom Path

Senior ML/AI Engineer #3624294

Richmond, VA · On-site +1

$114K - $227K/yr

This is a full-time opportunity available to candidates in Richmond, VA on a hybrid basis or remote ... Develop LLM-powered applications, prompt engineering strategies, retrieval-augmented generation ...

Kobie Marketing

AI Engineer

Richmond, VA · 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

Richmond, VA · 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 ...

TEKsystems

Data Engineer

Richmond, VA · Remote

$60 - $80/hr

Python & SQL: Strong hands-on experience building, deploying, and maintaining scalable data ... LLM integration in data workflows (using AI for data cleaning, anomaly detection, pipeline ...

New

Quora

AI Automation Engineer -Remote

Richmond, VA · On-site +1

$202K - $234K/yr

Experience creating LLM-backed tools involving prompt engineering and automated evals * 5+ years of ... Python, React and JavaScript * Excellent debugging skills and the ability to manage multiple ...

All JobsRemote Python Llm JobsRemote Python Llm Jobs in Chester, VA

Remote Python Llm information

See Chester, VA salary details

$12

$53

$79

How much do remote python llm jobs pay per hour?

As of Jul 3, 2026, the average hourly pay for remote python llm in Chester, VA is $53.94, according to ZipRecruiter salary data. Most workers in this role earn between $44.47 and $61.25 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 cities near Chester, VA are hiring for Remote Python Llm jobs? Cities near Chester, VA with the most Remote Python Llm job openings:
Remote Python Llm jobs near you

Full Stack Developer Python, React, Langchain

Ndimensions IT

Richmond, VA • Remote

Contractor

Posted 23 days ago

Job description

Full Stack Developer (Python, React, Langchain, Agentic AI) - Remote Contract

Location: Remote

Duration: 6 Months

Contract Type: W2, Contract, or C2C

Start Date: Immediate or as per availability

Client Industry: Third-Party Logistics (3PL), Supply Chain Management

About the Client

Our client is a fast-scaling innovator in the third-party logistics (3PL) space, leveraging intelligent automation to transform supply chain operations. They are building a next-generation logistics platform grounded in Agentic AI — enabling autonomous, goal-driven agents to optimize workflows, decision-making, and customer interactions.

Role Overview

We are seeking Full Stack Developers with a passion for building AI-native applications. This role focuses on developing a logistics platform powered by Agentic AI, using Langchain to orchestrate intelligent agents and Gen AI to enhance reasoning, retrieval, and automation. This is a remote, 6-month contract ideal for developers who thrive at the intersection of AI and real-world systems.

Responsibilities

- Design and develop full stack applications using Python and React

- Build and deploy Agentic AI workflows using Langchain and LLMs

- Architect autonomous agents for logistics use cases such as routing, exception handling, and predictive insights

- Integrate Gen AI capabilities for dynamic reasoning, semantic search, and task planning

- Collaborate with cross-functional teams to translate logistics requirements into scalable, intelligent systems

- Ensure performance, reliability, and maintainability of AI-driven applications

Required Skills

- Proficiency in Python and React for full stack development

- Hands-on experience with Langchain and LLM-based agent frameworks

- Strong understanding of Agentic AI principles and Gen AI tooling (e.g., OpenAI, Hugging Face, vector stores)

- Experience with RESTful APIs, microservices, and cloud-native deployment

- Familiarity with CI/CD pipelines, Git, and agile development practices

- Excellent communication and problem-solving skills

Preferred Qualifications

- Experience in logistics, supply chain, or transportation systems

- Exposure to RAG pipelines, semantic search, or autonomous agent orchestration

- Familiarity with containerization (Docker) and orchestration (Kubernetes)