Expert ML Software Engineer (Machine Learning)

Location: Onsite in Springfield, Virginia, United States. US citizenship and a TS/SCI clearance are required; ability to obtain a CI polygraph is required.

Salary: $150,000–$165,000 USD per year

Company

hirify.global delivers mission and technical expertise for national security and defense challenges, with capabilities spanning technology and defense operations.

What you will do

• Design, train, deploy, and maintain machine learning models for classification, regression, forecasting, deep learning, and anomaly detection.
• Build end-to-end ML pipelines covering data preprocessing, feature engineering, training, evaluation, and automated retraining.
• Deploy models as APIs or backend services and integrate ML systems with applications, databases, and cloud platforms.
• Monitor model performance, detect data or model drift, and manage model versioning and registries.
• Develop and operate MLOps workflows using Kubernetes and orchestration tools.

Requirements

• US citizenship, TS/SCI clearance, and ability to obtain a CI polygraph.
• Bachelor’s degree in a relevant field and 8 years of experience, or equivalent relevant expertise.
• Expertise in Python, Kubernetes, Git, Linux, REST APIs, backend development, API design, database integration, and Docker containerization.
• Experience with supervised and unsupervised learning, neural networks, NLP, PyTorch or TensorFlow, scikit-learn, pandas, and NumPy.
• Experience with MLOps tooling, experiment tracking, model registries, and pipeline orchestration using MLflow or equivalent, Kubeflow, Argo Workflows, or Airflow.
• Knowledge of data cleaning, feature engineering, linear algebra, probability, calculus, and prevention of data leakage.

Nice to have

• Master’s degree in a relevant field with 6 years of experience.
• Experience with low-latency model serving, LLM serving frameworks, GPU memory management, batching, and quantization.
• Experience with GPU orchestration and scheduling on shared or multi-tenant Kubernetes clusters.
• Experience with AWS, Azure, Google Cloud ML services, SageMaker, Vertex AI, and cloud CI/CD DevOps pipelines.

Culture & Benefits

• Medical, dental, and vision coverage with a company-contributed Health Savings Account.
• Annual paid time off, paid holidays, and paid parental leave.
• 401(k) plan with a company match and financial wellness support.
• Training and development opportunities, award programs, and company-sponsored events.
• Focus on work-life balance and professional growth.