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Llm Developer Jobs in Washington (NOW HIRING)

CogniSoft Technologies

Python Developer with AI/LLM

Mclean, VA · On-site

$51.50 - $71/hr

Python Developer with AI/LLM Location: Mc Lean, VA Developer-Full Stack Specialist Required Experience & Education • 5+ years of professional software development experience. • 1+ years of hands ...

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How much do llm developer jobs pay per hour?

As of Jul 15, 2026, the average hourly pay for llm developer in Washington is $56.82, according to ZipRecruiter salary data. Most workers in this role earn between $44.66 and $68.89 per hour, depending on experience, location, and employer.

What is the salary of LLM developer?

The salary of an LLM developer typically ranges from $80,000 to $150,000 annually, depending on experience, location, and the complexity of projects. Skilled developers with expertise in machine learning, natural language processing, and relevant tools like Python and TensorFlow tend to earn higher salaries.

What is a $900000 AI job?

A $900,000 AI job typically refers to high-level roles such as senior AI researchers or machine learning executives, often involving advanced skills in deep learning, large language models, and extensive experience. These positions may include leadership responsibilities, require specialized certifications, and offer compensation packages that include salary, bonuses, and stock options. Such roles are usually found in top tech companies or AI-focused organizations and demand a strong track record of innovation and technical expertise.

What does an LLM Developer do?

An LLM Developer designs, fine-tunes, and implements large language models (LLMs) for various applications, such as chatbots, content generation, and AI-driven tools. They work with machine learning frameworks, optimize model performance, and ensure efficient deployment. This role requires expertise in natural language processing (NLP), deep learning, and programming languages like Python.

What are the key skills and qualifications needed to thrive in the Llm Developer position, and why are they important?

To excel as an LLM Developer, you need strong expertise in natural language processing (NLP), deep learning frameworks, and programming languages such as Python, typically supported by a degree in computer science or a related field. Familiarity with machine learning libraries (like TensorFlow or PyTorch), cloud computing platforms, and experience with prompt engineering or fine-tuning large language models is crucial. Excellent problem-solving abilities, collaboration, and effective communication skills help you design solutions and work efficiently within multidisciplinary teams. These qualifications are essential for successfully building, deploying, and optimizing large language models that drive impactful AI applications.

What engineers make $500,000?

Senior machine learning engineers, including those developing large language models (LLMs), can earn $500,000 or more annually, especially with extensive experience, advanced skills in deep learning, and work at top tech companies. High compensation often includes base salary, bonuses, and stock options, particularly in competitive markets or leadership roles.

What are the typical daily tasks and responsibilities of an LLM Developer?

As an LLM Developer, your daily responsibilities often include designing, fine-tuning, and evaluating large language models to meet specific application needs. You may work on tasks such as data preprocessing, model training, performance benchmarking, and error analysis, frequently collaborating with data scientists, research engineers, and product managers. Keeping up to date with the latest advancements in NLP and integrating new techniques into production models is also a key part of the role. These tasks are usually performed in a team-oriented environment where clear communication and iterative experimentation are highly valued.

What are LLM developers?

LLM developers are software engineers who design, build, and optimize large language models used in artificial intelligence applications. They typically work with machine learning frameworks, programming languages like Python, and tools such as TensorFlow or PyTorch to develop models for tasks like natural language processing and understanding.
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Llm Developer jobs near you
Infographic showing various Llm Developer job openings in Washington as of July 2026, with employment types broken down into 82% Full Time, 8% Part Time, 1% Temporary, and 9% Contract. Highlights an 80% Physical, 5% Hybrid, and 15% Remote job distribution, with an average salary of $118,180 per year, or $56.8 per hour.
AI / LLM Engineer

AI / LLM Engineer

ClientServer Technology Solutions LLC

Mclean, VA • On-site

Other

Posted 29 days ago

Job description

Role: AI / LLM Engineer

Location: McLean, VA (Locals Only)

Visa:

Required Qualifications

  • 3 5 years of software engineering experience, with at least 1 2 years building with LLMs or applied ML in a production or near-production setting.
  • Strong proficiency in Python (or comparable) and solid engineering fundamentals testing, version control, clean and maintainable code.
  • Hands-on experience building RAG systems: embeddings, vector databases, and chunking/indexing strategies, with a real sense of how to diagnose and improve retrieval quality.
  • Experience building data ingestion/ETL pipelines and working with large, messy, realworld datasets.
  • Experience integrating third-party APIs into backend services, including authentication flows (OAuth/SSO) and webhook/event-driven patterns.
  • Hands-on experience with LLM APIs (e.g., Anthropic, OpenAI, or similar) and at least one orchestration framework.
  • Experience evaluating model and retrieval outputs building eval sets, measuring quality, iterating.
  • A careful approach to data access, permissions, and handling sensitive information.
  • Familiarity with at least one major cloud platform (AWS preferred). Preferred Qualifications
  • Experience with Amazon Bedrock or other managed LLM platforms.
  • Experience integrating with enterprise collaboration platforms (chat, wikis, ticketing) via their APIs.
  • Experience with knowledge graphs or entity-relationship modeling for retrieval.
  • Experience building multi-user or multi-tenant systems with scoped permissions and audit requirements.
  • Familiarity with observability/tracing for LLM or data pipelines.
  • Basic Lops exposure: Docker, CI/CD, deploying services to production.
  • Bachelor s degree in Computer Science, Engineering, or a related field or equivalent practical experience.

Role: AI Engineer

Location: McLean, VA(Locals Only)

Visa:

Visa:

  • 10+ years in applied machine learning / data science, with deep hands-on experience in recommender systems, learning-to-rank, or large-scale personalization.
  • Practical experience building with LLMs in production: generating and integrating model derived features or profiles, working with embeddings, and reasoning about evaluation, latency, and cost.
  • Experience with Amazon Bedrock or comparable managed LLM platforms for production inference.
  • Hands-on experience with segment- or cohort-based personalization, including measuring performance at the segment level rather than relying on aggregate metrics.
  • Experience designing cold-start strategies for users or items with limited history.
  • Strong communication skills able to explain modeling decisions, trade-offs, and results clearly to engineers, data scientists, and senior business stakeholders, and to manage expectations through ambiguity.
  • Customer-facing or stakeholder-facing experience: building trust, navigating competing priorities, and serving as a senior technical voice in high-stakes conversations.
  • A track record of technical leadership through mentoring engineers, driving design decisions, and setting standards.
  • Strong track record taking ML models from experimentation to production, owning the offline-to-online validation story (ranking metrics, ablations, segment analysis, shadow testing, A/B readiness). Deep, hands-on expertise in deep learning for ranking/recommendation multi-task learning, embedding-based architectures with a major framework (TensorFlow or PyTorch).
  • Strong feature engineering on large behavioral datasets using the modern data stack (PySpark, SQL, distributed data lakes).
  • Rigorous experimental methodology hyperparameter optimization, bias correction, and a disciplined, hypothesis-driven approach to measuring true lift.
  • Hands-on AWS experience across the ML lifecycle, and strong proficiency in Python. Preferred Qualifications
  • Experience personalizing ranking for marketplaces or consumer platforms at scale (ecommerce, food delivery, media, or similar).
  • MLOps maturity: model versioning, monitoring, and reproducible training pipelines.
  • Advanced degree in Computer Science, Machine Learning, Statistics, or a related quantitative field.
  • Prior experience in a client-facing consulting or professional-services delivery environment

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