Leidos' Security Enterprise Solutions (SES) operation is seeking a Machine Learning Engineer to support their data science and AI initiatives, specifically in developing new capabilities and intellectual property for the detection of prohibited concealed items on passengers or in their baggage, and building intelligent systems that drive real-world impact in automated security solutions.
Requirements
- Solid understanding of machine learning fundamentals (e.g., supervised/unsupervised learning, model evaluation).
- Proficiency in Python and common ML libraries (e.g., scikit-learn, pandas, NumPy).
- Proficiency in Object-oriented software design.
- Familiarity with PyTorch, or similar frameworks.
- Familiarity with cloud platforms (e.g., AWS, GCP, or Azure).
- Experience with version control tools (e.g., Git).
- Exposure to MLOps concepts or tools (e.g., MLflow, Docker, CI/CD).
Responsibilities
- Assist in designing, developing, testing, and deploying machine learning models.
- Work with large datasets: cleaning, preprocessing, feature engineering.
- Collaborate with data scientists, engineers, and product managers to integrate ML models into applications.
- Help monitor model performance and retrain/update models as needed.
- Contribute to documentation and best practices.
- Stay up to date with the latest ML research, tools, and technologies.
- Familiarity with deep learning frameworks, especially PyTorch, and the ability to build and fine-tune neural network models.
Other
- Must have the ability to obtain a Public Trust clearance (US citizenship required).
- May require occasional travel (10%), domestic or international.
- Strong problem-solving and communication skills.
- Eagerness to learn and adapt in a fast-paced environment.
- Strong documentation skills and the ability to clearly communicate technical details to both technical and non-technical audiences.
