Artificial Intelligence Machine Learning Skill Level 2

Required Clearance: Active TS/SCI with Full Scope Polygraph (in scope within the past 7 years)
Hourly Pay Range: $20.00–$50.00

Wyetech is seeking an experienced Artificial Intelligence/Machine Learning (AI/ML) Engineer Level 2 to support the research, design, development, testing, evaluation, integration, deployment, and sustainment of advanced AI/ML algorithms and scalable machine learning solutions supporting mission-critical Government requirements.

The successful candidate will develop and optimize machine learning models capable of identifying patterns, learning from data, and generating predictions aligned with customer requirements. This position requires experience across the machine learning lifecycle, including dataset selection, statistical analysis, model architecture, training and retraining, performance evaluation, integration, deployment, and ongoing optimization.

The AI/ML Engineer will research and implement AI/ML algorithms, evaluate data and model quality, transform data science prototypes into scalable operational solutions, and oversee iterative testing and validation activities. The selected candidate will also support data pipeline integration, software architecture considerations, data modeling, and the identification of changes in data distributions that may affect model performance.

The ideal candidate will possess experience with standard machine learning frameworks such as PyTorch and Tensor Flow, strong analytical and problem-solving capabilities, and the ability to collaborate effectively with software engineers, data scientists, systems engineers, and mission stakeholders.

• Demonstrated experience designing, developing, testing, evaluating, and deploying artificial intelligence and machine learning algorithms.

• Experience supporting applied machine learning initiatives in programs or contracts of similar scope, type, and complexity.

• Experience selecting appropriate datasets for model training, testing, and evaluation.

• Experience performing statistical analysis to identify patterns, evaluate datasets, and support model development.

• Experience implementing and executing machine learning algorithms.

• Experience using model evaluation results to improve model performance, accuracy, reliability, and efficiency.

• Experience training, retraining, fine-tuning, and optimizing machine learning models.

• Experience working with machine learning libraries, frameworks, and software packages.

• Experience using standard machine learning frameworks such as PyTorch and Tensor Flow.

• Experience conducting model testing, evaluation, verification, and validation.

• Experience overseeing iterative AI/ML testing and evaluation activities.

• Experience researching and implementing machine learning algorithms, methodologies, and supporting tools.

• Experience selecting appropriate data and knowledge representation methods.

• Understanding of software architecture, data modeling, data structures, and system integration.

• Experience transforming data science prototypes into scalable software solutions.

• Experience evaluating data quality and verifying machine learning model outputs.

• Experience identifying differences in data distributions that affect model performance.

• Experience supporting integration of AI/ML models into existing applications and operational environments.

• Familiarity with data pipelines, infrastructure management, data engineering, and data governance.

• Experience documenting model architectures, development processes, evaluation results, and technical findings.

• Strong analytical, troubleshooting, communication, and problem-solving skills.

• Ability to collaborate with technical teams and stakeholders to…