Leidos' Security Enterprise Solutions (SES) is seeking a Machine Learning Engineer to support their data science and AI initiatives, focusing on developing new capabilities and intellectual property for automated security solutions, such as detecting prohibited concealed items on passengers or in baggage.
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).
- Basic knowledge of SQL and data querying.
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.
