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Language Model Jobs in Maryland (NOW HIRING)

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Language Model information

What are language models?

Language models are artificial intelligence systems designed to understand, generate, and manipulate human language. They are trained on vast amounts of text data to predict the next word in a sequence, answer questions, write content, translate languages, and perform other language-related tasks. Modern language models, such as those based on deep learning, have revolutionized natural language processing by enabling more accurate and context-aware interactions between humans and machines.

What is the difference between Language Model vs Data Scientist?

AspectLanguage ModelData Scientist
Required CredentialsNone specific; knowledge of NLP and AI concepts helpfulBachelor's or higher in Data Science, Statistics, or related fields
Work EnvironmentAI development teams, research labs, tech companiesBusiness, finance, healthcare, and various industries
Employer & Industry UsageUsed in AI applications, chatbots, content generationAnalyzing data, building models, providing insights

While both roles involve working with data and AI, a Language Model is an AI system designed to understand and generate human language, often developed by AI engineers. A Data Scientist analyzes data to extract insights and build predictive models, often utilizing language models as tools. Understanding the differences helps clarify career paths and job expectations in the AI and data fields.

What are the key skills and qualifications needed to thrive as a Language Model, and why are they important?

To thrive as a Language Model Engineer, you need a strong background in computer science, machine learning, and natural language processing, often supported by a relevant degree. Experience with frameworks like TensorFlow or PyTorch, and familiarity with large-scale data processing tools, are typically required. Strong analytical thinking, collaboration, and problem-solving skills help in designing effective models and working with cross-functional teams. These capabilities are crucial for developing performant and accurate language models that meet complex real-world communication needs.

What are the common challenges faced by professionals working on language model development teams?

Professionals developing language models often encounter challenges such as managing large datasets, addressing biases in training data, and optimizing model performance while balancing computational resources. Collaboration with cross-functional teams—including data scientists, engineers, and domain experts—is essential to ensure the model's accuracy and relevance. Additionally, staying current with rapid advancements in AI research and maintaining responsible AI practices are crucial aspects of the role.
What are popular job titles related to Language Model jobs in Maryland? For Language Model jobs in Maryland, the most frequently searched job titles are:
What cities in Maryland are hiring for Language Model jobs? Cities in Maryland with the most Language Model job openings:
Infographic showing various Language Model job openings in Maryland as of July 2026, with employment types broken down into 20% Internship, 70% Full Time, and 10% Part Time. Highlights an 70% In-person, and 30% Remote job distribution.
Cleared AI/ML Software Engineer

Cleared AI/ML Software Engineer

Yellow Duck Technologies Inc.

Annapolis Junction, MD • On-site

Full-time

Re-posted 13 days ago


Job description

Yellow Duck Technologies is seeking a Software Engineer with TS/SCI FSP clearance to join our artificial intelligence and machine learning (AI/ML) team. Responsibilities include training, hosting, and the optimization of Large Language Model (LLM) instances within our computing environment.
Requirements:
  • Must have an active TS/SCI clearance with Full Scope Polygraph.
  • 12+ years of experience in software engineering, with a focus on machine learning or natural language processing.
  • Degree in Computer Science, Artificial Intelligence, or a related field.
  • Strong expertise in deep learning frameworks such as TensorFlow, PyTorch, or MXNet.
  • Proficiency in programming languages such as Python, C++, or Java.
  • Solid understanding of LLM architectures, training techniques, and evaluation methodologies.
  • Familiarity with cloud platforms (e.g., AWS, GCP) and their machine learning services.
  • Knowledge of software engineering best practices, including version control, testing, and continuous integration/deployment.
  • Excellent problem-solving and debugging skills.
  • Strong communication and collaboration abilities to work effectively with cross-functional teams.
Yellow Duck is hiring cleared technical professionals at all skill levels. If you possess an active TS/SCI clearance with Full Scope Polygraph, please submit your resume for a friendly follow-up and quick job-matching response!
Yellow Duck Technologies provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, ethnicity, religion, sex, sexual orientation, gender identity and expression, national origin, disability, genetic information, veteran status, or any other protected characteristic or class.