AI/ML Software Engineer

Parsons Corporation•Aberdeen, MD

1d•$103,500 - $181,100

About The Position

Parsons is searching for a seasoned professional to support the development, integration, deployment, and ongoing execution of open-source and in-house machine learning software solutions. The ideal candidate will bring strong software engineering experience combined with hands-on expertise in building, evaluating, and optimizing AI/ML systems in production and research-driven environments.

Requirements

Required B.S./M.S. and 5+ of directly related post-degree professional experience.
Experience developing in Python and Bash, leveraging SDLC practices, and working within and administering Linux systems.
Experience building, integrating, or supporting machine learning models, data pipelines, or AI-enabled software applications.
Understanding of software engineering best practices, including version control, testing, code review, and CI/CD workflows.
Familiarity with model evaluation, performance tuning, and troubleshooting in development or production environments.
Ability to work both independently and as part of a multi-team development project.
Strong problem-solving, analytical, and communication skills.
U.S. Citizenship is required.
Must be able to obtain and maintain a security clearance.

Nice To Haves

Familiarity with microservices management such as Kubernetes and containerization technologies such as Docker.
Experience with ML frameworks and libraries such as PyTorch, TensorFlow, scikit-learn, or similar tools.
Familiarity with MLOps concepts, including model versioning, deployment automation, and monitoring.
Experience working with cloud-based or hybrid computing environments for AI/ML workloads.
Knowledge of distributed computing, scalable data processing, or GPU-accelerated workflows.
Experience supporting AI/ML solutions in secure, mission-focused, or government environments.

Responsibilities

Support the design, development, integration, testing, and maintenance of machine learning software applications and services.
Conduct experiments to evaluate the scalability, efficiency, accuracy, and effectiveness of deployed ML solutions.
Develop and refine data processing pipelines, model training workflows, and inference services to support mission and business needs.
Collaborate with cross-functional teams to transition AI/ML capabilities from prototype to production-ready systems.
Assist with model performance monitoring, debugging, and continuous improvement of deployed solutions.
Apply software optimization and data analysis methods to improve system performance, reliability, and maintainability.
Contribute to automation, documentation, and repeatable development practices across the AI/ML lifecycle.
Support integration of AI/ML components into larger software platforms and operational environments.