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Llm Ml Rag Jobs in Silver Spring, MD (NOW HIRING)

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Gen AI/Python Developer - JL

Reston, VA · On-site

$52.25 - $72/hr

SQL * AWS Data Services * LLM * ML * Sagemaker * Bedrock Top 3 Soft Skills: * Confidence in ... Familiarity with vector databases (e.g., FAISS, Pinecone) and retrieval-augmented generation (RAG)

Interon IT Solutions

AI/ML Engineer

Reston, VA · On-site

AI/ML Engineer (Python, AWS, GenAI) Location: Reston, VA (In-person interviews required) Candidate ... Architect and operationalize RAG pipelines , embeddings, vector databases, and LLM-powered ...

Closure Technologies

AI/ML Engineer

Mclean, VA · On-site

Experience developing AI/ML applications focused on Retrieval-Augmented Generation (RAG), semantic retrieval, LLM integration, or related AI workflows. * Strong proficiency in Python and modern AI/ML ...

GRVTY

AI/ML Engineer

Mclean, VA · On-site

... RAG), semantic retrieval, LLM integration, or related AI workflows • Strong proficiency in Python and modern AI/ML libraries, frameworks, and API integrations • Willingness to work onsite ...

Closure Technologies

AI/ML Engineer

Mclean, VA · On-site

... RAG), semantic retrieval, LLM integration, or related AI workflows. • Strong proficiency in Python and modern AI/ML libraries, frameworks, and API integrations. • Active/current TS/SCI with ...

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All JobsLlm Ml Rag JobsLlm Ml Rag Jobs in Silver Spring, MD

Llm Ml Rag information

See Silver Spring, MD salary details

$46.5K

$77.8K

$113.7K

How much do llm ml rag jobs pay per year?

As of Jul 26, 2026, the average yearly pay for llm ml rag in Silver Spring, MD is $77,843.00, according to ZipRecruiter salary data. Most workers in this role earn between $64,100.00 and $89,900.00 per year, depending on experience, location, and employer.

What are some typical challenges faced when working on Retrieval-Augmented Generation (RAG) systems in large language model (LLM) machine learning roles?

Professionals working on LLM ML RAG systems often encounter challenges such as ensuring the accuracy and relevancy of retrieved documents, managing latency for real-time queries, and seamlessly integrating retrieval mechanisms with generation models. Additionally, keeping up with evolving datasets and maintaining high-quality knowledge bases can be demanding. Collaboration with data engineers and domain experts is common to refine retrieval pipelines and optimize the end-to-end system.

What is the difference between Llm Ml Rag vs Data Scientist?

AspectLlm Ml RagData Scientist
Required CredentialsMaster's or PhD in ML, AI, or related fields; certifications in ML frameworksDegree in Computer Science, Statistics, or related; certifications in data analysis or ML
Work EnvironmentResearch labs, AI development teams, tech companiesBusiness analytics, research, product development teams
Employer & Industry UsageTech firms, AI startups, research institutionsFinance, healthcare, tech, consulting firms
Common Search & ComparisonOften compared for ML specialization and research focusCompared for data analysis, modeling, and business insights

While both roles involve working with machine learning, Llm Ml Rag typically focuses on research and development of large language models, requiring advanced ML expertise. Data Scientists often work on analyzing data, building predictive models, and deriving insights for business decisions. The roles overlap in skills but differ in focus and application areas.

What are the key skills and qualifications needed to thrive as an LLM ML RAG (Retrieval-Augmented Generation) Engineer, and why are they important?

To excel as an LLM ML RAG Engineer, you need a strong background in machine learning, natural language processing, and large language models, typically supported by a degree in computer science or a related field. Proficiency with tools and frameworks like Python, PyTorch/TensorFlow, Hugging Face Transformers, and vector databases (e.g., FAISS, Pinecone) is essential, along with experience in deploying and fine-tuning LLMs and integrating retrieval systems. Strong problem-solving skills, attention to detail, and the ability to collaborate with cross-functional teams distinguish top performers in this role. These skills ensure the effective development and deployment of advanced AI solutions that combine generative and retrieval capabilities for high-impact applications.

What are LLM ML RAG jobs?

LLM ML RAG jobs involve working with Large Language Models (LLMs), Machine Learning (ML), and Retrieval-Augmented Generation (RAG) systems. Professionals in these roles typically design, develop, and optimize AI systems that combine language models with retrieval techniques to improve accuracy, relevance, and factual grounding in generated outputs. These jobs often require expertise in natural language processing, deep learning, data engineering, and information retrieval. Key responsibilities might include integrating RAG pipelines, fine-tuning LLMs, and ensuring high-quality responses from AI applications.
What are popular job titles related to Llm Ml Rag jobs in Silver Spring, MD? For Llm Ml Rag jobs in Silver Spring, MD, the most frequently searched job titles are:
What job categories do people searching Llm Ml Rag jobs in Silver Spring, MD look for? The top searched job categories for Llm Ml Rag jobs in Silver Spring, MD are:
What cities near Silver Spring, MD are hiring for Llm Ml Rag jobs? Cities near Silver Spring, MD with the most Llm Ml Rag job openings:
Llm Ml Rag jobs near you

A.I. Engineer (LLM/ RAG/ AI/ML with Security Clearance

Kforce Federal Solutions

Fort George G Meade, MD • On-site

Other

Medical, Dental, Vision, Life, Retirement, PTO

Posted 13 days ago

Job description

Senior AI Engineer (LLM / RAG / AI/ML)
Location: Fort Meade, MD (Onsite)
Clearance: TS/SCI with Full Scope Polygraph Apply Now!
or Contact Recruiter: Brenton Anderson
Email:
LinkedIn: https://www.linkedin.com/in/myitrecruiterbrenton/ We are seeking a Senior AI Engineer to support advanced AI and emerging technology initiatives, focusing on building and deploying cutting-edge AI/ML solutions. This role emphasizes Large Language Models (LLMs), data engineering, and scalable AI architectures in a secure, mission-driven environment.
This is a highly technical, hands-on role ideal for engineers with strong software engineering foundations and experience operationalizing AI/ML capabilities. Key Responsibilities Design, develop, and maintain AI/ML solutions supporting advanced analytics and automation efforts
Build and optimize LLM orchestration frameworks integrating multiple AI components
Develop systems combining RAG (Retrieval-Augmented Generation), static analysis tools, and automated testing pipelines
Engineer data pipelines to ingest, clean, transform, and vectorize structured and unstructured data
Fine-tune and optimize Large Language Models (LLMs) for specialized use cases
Design and implement database solutions supporting vector search, metadata, and artifact storage
Support development of tools for vulnerability identification and mitigation using AI/ML techniques
Deploy and manage AI solutions within secure, containerized, and networked environments
Conduct performance tuning, scalability analysis, and system optimization
Support security assessments and ATO processes for deployed AI systems
Collaborate with cross-functional teams in an Agile development environment Required Qualifications Active TS/SCI with Full Scope Polygraph
Bachelor’s degree and 8+ years of relevant experience (or equivalent)
Strong proficiency in Python development
Hands-on experience with AI/ML systems and LLM integration
Experience building or working with RAG architectures and data pipelines
Experience with data preprocessing, transformation, and vectorization techniques
Knowledge of relational and vector databases
Experience with containerization and orchestration (Docker, Kubernetes)
Familiarity with Agile methodologies and tools (Git, Jira, Confluence)
Strong software engineering fundamentals and experience delivering production systems Preferred Qualifications Experience with static code analyzers and automated testing pipelines
Familiarity with modern LLM tools and platforms (e.g., Claude, Codex or similar)
Experience with CI/CD pipelines and DevOps practices
Exposure to Rust or other systems-level programming languages
Experience building AI solutions in high-security or controlled environments
Knowledge of advanced AI-driven cybersecurity or vulnerability detection techniques Education Bachelor’s degree in Computer Science, Engineering, or related field
Equivalent experience may be considered Why This Role Work on next-generation AI/ML and LLM-driven systems
Direct impact on advanced analytics and security-focused AI capabilities
Highly technical environment with ownership of end-to-end AI solutions
Long-term, stable onsite opportunity in the Fort Meade market The pay range is the lowest to highest compensation we reasonably in good faith believe we would pay at posting for this role. We may ultimately pay more or less than this range. Employee pay is based on factors like relevant education, qualifications, certifications, experience, skills, seniority, location, performance, union contract and business needs. This range may be modified in the future. We offer comprehensive benefits including medical/dental/vision insurance, HSA, FSA, 401(k), and life, disability & ADD insurance to eligible employees. Salaried personnel receive paid time off. Hourly employees are not eligible for paid time off unless required by law. Hourly employees on a Service Contract Act project are eligible for paid sick leave. Note: Pay is not considered compensation until it is earned, vested and determinable. The amount and availability of any compensation remains in Kforce's sole discretion unless and until paid and may be modified in its discretion consistent with the law. This job is not eligible for bonuses, incentives or commissions. Kforce is an Equal Opportunity/Affirmative Action Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, pregnancy, sexual orientation, gender identity, national origin, age, protected veteran status, or disability status. By clicking “Apply Today” you agree to receive calls, AI-generated calls, text messages or emails from Kforce and its affiliates, and service providers. Note that if you choose to communicate with Kforce via text messaging the frequency may vary, and message and data rates may apply. Carriers are not liable for delayed or undelivered messages. You will always have the right to cease communicating via text by using key words such as STOP.

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