Artificial Intelligence​/Machine

At Wyetech, you’ll be at the center of an award‑winning corporate culture, breaking technological barriers and solving real‑world problems for our federal government customers. We are committed to hiring the best of the best, and in return, we offer a world‑class, truly unique employee experience that is rare within our industry.

We are seeking an AI/ML Level 1 Engineer, responsible for building, training, fine‑tuning, and evaluating advanced language models. The ideal candidate will have hands‑on experience with state‑of‑the‑art machine learning techniques, specifically for natural language processing (NLP), and will also have a strong understanding of full‑stack development. This person will work across the model development lifecycle and collaborate with cross‑functional teams to deliver high‑impact solutions.

The Artificial Intelligence/Machine Learning (AI/ML) Engineer designs, creates, tests, and productizes AI/ML algorithms to solve business challenges. The AI/ML models they create should be capable of learning and making predictions as defined by the business logic developed to meet customer requirements. The AI/ML Engineer should be proficient in all aspects of model architecture, data pipeline interaction, and metrics application, interpretation, and presentation.

The AI/ML Engineer needs familiarity with foundational concepts of application development, infrastructure management, data engineering, and data governance. Through an understanding of training, retraining, deploying, scheduling, monitoring, and improving models through iterative user and system feedback, the AI/ML Engineer designs and creates scalable solutions for optimal performance. The AI/ML Engineer may be responsible for leading geographically diverse teams and will often serve as a primary POC for AI‑related matters, so must have exceptional analytical, problem‑solving and communication skills.

Expert knowledge of multiple programming languages, e.g. Python, Java, C, R, a plus.

Due to federal contract requirements, United States Citizenship and position appropriate security clearance is required. (e.g. Active TS/SCI security clearance with agency appropriate polygraph).

• Select appropriate data sets
• Perform statistical analysis
• Run machine learning algorithms
• Use results to improve models
• Train and retrain systems when needed
• Experience in working with various ML libraries and packages
• Run standard test and evaluation protocols
• Provide system integration oversight

• TS/SCI with agency appropriate poly
• 2 years experience in applied machine learning in programs and contracts of similar scope, type, and complexity is required.
• A B.S. degree in advanced math (e.g., calculus, linear algebra or Bayesian statistics), computer science or related STEM discipline from an accredited college or university is required.
• 3 years of additional machine learning experience on projects with similar machine learning processes may be substituted for a bachelor’s degree.

• Knowledge and experience of Language models is required
• Specific experience with Marian and multi‑lingual model development
• Knowledge of Computation Linguistics is a plus
• Experience with Open‑Source model libraries, Deep Learning Containers (DLC), GPU technologies and optimization / tuning
• Strong Java, C, C++ programming experience
• Willingness to support occasional on‑call duties is a plus
• Model Development & Training:
• Build, train, and fine‑tune machine learning models, particularly language models
• Apply best practices in model training, tuning, and optimization.
• Design and implement solutions for model performance improvement.
• Evaluation & Testing:
• Conduct rigorous model evaluation, including performance analysis and benchmarking.
• Perform error analysis, debugging, and model diagnostics to ensure quality and reliability.
• Model Deployment & Integration:
• Work with cloud‑based AI platforms (especially AWS Sagemaker) to deploy and scale models.
• Integrate machine learning models into production environments, ensuring seamless integration with other systems.
• Full‑Stack Engineering:
• Contribute to the development and maintenance of the full stack…