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 for detecting prohibited concealed items on passengers or in baggage, and building intelligent systems for 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.
Other
- May require occasional travel (10%), domestic or international.
- Must have the ability to obtain a Public Trust clearance (US citizenship required).
- Strong problem-solving and communication skills.
- Eagerness to learn and adapt in a fast-paced environment.
- Proven experience building, validating, and deploying machine learning models in real-world scenarios.
