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Python Llm Jobs in McLean, VA (NOW HIRING)

Tech Tammina

AI/ML Engineer

Reston, VA · On-site

... Python microservices (FastAPI/Flask) enabling scalable data pipelines, model inference, and real-time analytics. Architect and operationalize RAG pipelines, embeddings, vector databases, and LLM ...

Interon IT Solutions

AI/ML Engineer

Reston, VA · On-site

... Python microservices using FastAPI/Flask for data pipelines, real-time analytics, and model inference. * Architect and operationalize RAG pipelines , embeddings, vector databases, and LLM-powered ...

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Python Llm information

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How much do python llm jobs pay per hour?

As of Jul 14, 2026, the average hourly pay for python llm in McLean, VA is $59.26, according to ZipRecruiter salary data. Most workers in this role earn between $48.85 and $67.31 per hour, depending on experience, location, and employer.

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

Full Stack Python Developer with Security Clearance

Nicholson Strategic Solutions

Herndon, VA • On-site

Contractor

Posted 15 days ago

Job description

What You’ll Do:
Government contractor is seeking a Full Stack Python Developer to build and scale user-facing and backend applications that power AI/ML capabilities for the DoD Search Portfolio.
You will develop secure, cloud-native web services and UI experiences that integrate with LLM/RAG and semantic search pipelines. This role partners closely with ML engineers and data teams to productionize models through robust APIs, workflows, and operational tooling. You will help deliver mission-ready solutions that handle large-scale datasets with strong performance, reliability, and traceability.
The ideal candidate thrives in fast-paced environments and enjoys building end-to-end systems that make AI usable for real users. Responsibilities will include but are not limited to:
Support CI/CD and DevOps practices (containerization, deployment automation, monitoring/alerting) to ensure stable releases and operational readiness.
Apply best practices for security, logging, auditing, and compliance aligned with federal/DoD standards across services and environments.
Design and develop Python backend services and REST APIs (e.g., Flask/FastAPI) to expose AI/ML and search capabilities to applications and mission systems.
Build full stack features (UI + API) that support search workflows, semantic retrieval, and results visualization for enterprise users.
Integrate backend services with Databricks/Spark pipelines and ML workflows to enable scalable inference, data processing, and batch/stream execution.
Implement and maintain integrations with Elasticsearch (search/indexing) and Neo4j (graph/relationship-driven experiences) to enhance relevance and discovery.
Collaborate with ML Engineers to productionize LLM/RAG-based features, including prompt/inference orchestration, embeddings services, and retrieval workflows.
Create clear technical documentation and communicate design decisions, trade-offs, and implementation approaches to both technical and non-technical stakeholders.
What You’ll Need:
Bachelor’s degree (or equivalent experience) with 5+ years in software engineering focused on Python and web application development.
Must have: Strong hands-on experience building Python APIs/services (Flask/FastAPI preferred) and integrating with databases, search platforms, and external systems.
Experience developing full stack applications using modern front-end frameworks (React/Angular/Vue) plus strong API design skills.
Familiarity with AI/ML concepts and integrations (LLMs, embeddings, semantic search, RAG workflows) and working closely with data/ML teams.
Must have: Working experience with cloud-native delivery (Docker/Kubernetes), CI/CD, Git-based workflows, and performance/reliability best practices; Databricks/Spark experience required.

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