Artificial Intelligence/Machine Learning Engineer 1 - (NLP, AWS, PyTorch)

Akina • Annapolis Junction, MD

7d • Onsite

About The Position

Designs, creates, tests, and productizes AI/ML algorithms to solve business challenges and support customer requirements. The role works across model architecture, data pipeline interaction, and metrics application, interpretation, and presentation, requiring familiarity with application development, infrastructure management, data engineering, and data governance. It uses training, retraining, deployment, scheduling, monitoring, and iterative improvement to create scalable solutions, and may lead geographically diverse teams as a primary point of contact for AI-related matters.

The engineer builds, trains, and fine-tunes machine learning models, particularly language models; evaluates and improves model performance; and deploys and scales models using cloud-based AI platforms, especially AWS SageMaker. The role integrates models into production and contributes to the front end, back end, and deployment pipelines for AI model-based applications. It also works with data scientists, product teams, and engineers to translate business requirements into technical solutions, documents workflows and technical specifications, selects data sets, conducts statistical analysis, runs machine learning algorithms and test protocols, and provides system integration oversight.

The position requires a TS/SCI clearance, with a polygraph required within seven years. It is located in Annapolis Junction, Maryland. The advertised annual salary range is $170,000–$208,000; actual compensation may vary based on experience, location, and contractual requirements.

Requirements

• Active TS/SCI clearance; polygraph required within seven years.
• Two years of applied machine learning experience on programs and contracts of similar scope, type, and complexity.
• Bachelor’s degree in advanced mathematics, computer science, or a related STEM discipline from an accredited college or university; alternatively, three additional years of machine learning experience on projects with similar machine learning processes may substitute for the bachelor’s degree.
• Knowledge and experience with language models, including Marian and multilingual model development.
• Knowledge of computational linguistics.
• Experience with open-source model libraries.
• Experience with Deep Learning Containers (DLC) and GPU technologies.
• Experience in optimization and tuning.
• Strong Java, C, and C++ programming experience.
• Strong proficiency in AI/ML frameworks such as TensorFlow, PyTorch, or Hugging Face.
• Hands-on experience with AWS tools such as SageMaker, Lambda, EC2, and S3.
• Experience developing full-stack software applications using technologies such as JavaScript, Python, and Java.
• Solid understanding of data structures, algorithms, and system design.
• Extensive experience developing machine learning models, including natural language processing (NLP).
• Experience with model evaluation, optimization, and performance monitoring.
• Experience with model versioning and management using tools such as MLflow or Git.
• Familiarity with containerization tools such as Kubernetes.

Nice To Haves

• Willingness to support occasional on-call duties.
• Experience in a government or defense-related environment.
• Experience with secure data handling and compliance requirements.
• Experience working with Large Language Models (LLMs).

Responsibilities

• Build, train, and fine-tune machine learning models, particularly language models.
• Apply best practices in model training, tuning, and optimization.
• Design and implement solutions to improve model performance.
• Evaluate models through performance analysis and benchmarking.
• Conduct error analysis, debugging, and model diagnostics to ensure quality and reliability.
• Use AWS tools, especially SageMaker, to deploy and scale models.
• Integrate machine learning models into production environments and other systems.
• Contribute to the development and maintenance of the front end and back end of AI model-based applications.
• Collaborate with software engineers to build scalable, efficient deployment pipelines.
• Work with data scientists, product teams, and engineers to translate business requirements into technical solutions.
• Document workflows, model design processes, and technical specifications.
• Select appropriate data sets and perform statistical analysis.
• Run machine learning algorithms and use results to improve models.
• Train and retrain systems when needed.
• Run standard test and evaluation protocols.
• Provide system integration oversight.
• Train, deploy, schedule, monitor, and iteratively improve scalable AI/ML solutions.
• Potentially lead geographically diverse teams and serve as the primary point of contact for AI-related matters.

Benefits

• 24 days of PTO accrued annually.
• 11 federal holidays.
• 401(k) is 100% vested on the start date.
• Company direct 401(k) contribution worth 10% of salary.
• Company covers 100% of employee healthcare costs and 50% of dependent healthcare costs.
• Educational assistance toward college classes.
• Coverage of costs associated with job-related training and certifications.

What This Job Offers

• Job Type: Full-time
• Career Level: Entry Level