Leidos
Description
Join Leidos' Security Enterprise Solutions (SES) team as a
Machine Learning Specialist
and be a pivotal part of our data science and AI initiatives. In this role, you will collaborate with talented professionals to design, build, and maintain machine learning models and pipelines. Your expertise will contribute to crafting innovative solutions that help detect prohibited concealed items on passengers or within their baggage. Our mission is to redefine automated security solutions through cutting-edge technology, and we are seeking passionate, curious, and team-oriented individuals to help us achieve this goal. Primary Responsibilities: Design, develop, test, and deploy machine learning models. Work with large datasets, focusing on cleaning, preprocessing, and feature engineering. Collaborate with cross-disciplinary teams, including data scientists, engineers, and product managers to integrate ML models into applications. Monitor model performance, retrain, and update models as necessary. Contribute to documentation and establish best practices. Stay updated on the latest research, tools, and technologies in machine learning. Occasional travel (approximately 10%) may be required, both domestically and internationally. Requirements: Bachelor's degree in Computer Science, Engineering, Mathematics, or a related field with 2+ years of experience, or a Master's degree with less than 2 years of experience. Additional work experience may substitute for a degree. Ability to obtain a Public Trust clearance (U.S. citizenship required). Solid understanding of machine learning fundamentals, including supervised and unsupervised learning, as well as model evaluation techniques. Proficiency in Python along with key ML libraries such as scikit-learn, pandas, and NumPy. Experience in object-oriented software design. Familiarity with PyTorch or similar frameworks. Experience with cloud platforms, including AWS, GCP, or Azure. Proficient in version control tools such as Git. Exposure to MLOps concepts or tools like MLflow, Docker, and CI/CD pipelines. Basic knowledge of SQL for data queries. Strong problem-solving abilities and excellent communication skills. A genuine eagerness to learn and adapt in a dynamic environment. Preferred Qualifications: Master's degree and 1-2 years of hands-on experience in machine learning or data science (including internships, research, or full-time roles). Proven experience in building, validating, and deploying machine learning models in real-world settings. Completed projects showcasing the application of ML techniques to tackle complex problems. Certifications in cloud platforms, such as Microsoft Certified: Azure AI Engineer Associate, AWS Certified Machine Learning - Specialty, or Google Cloud Professional Machine Learning Engineer. Hands-on experience with MLOps tools and workflows, notably MLflow, Docker, CI/CD pipelines, and model monitoring. Familiarity with deep learning frameworks, especially PyTorch, and the ability to develop and refine neural network models. Exposure to data engineering workflows, such as data pipeline tools (e.g., Airflow), distributed processing (e.g., Spark), and data lake architectures. Strong documentation skills with the capacity to communicate technical details effectively to both technical and non-technical audiences. Involvement in open-source ML projects, Kaggle competitions, or relevant publications is a plus. The
Leidos Security Enterprise Solutions (SES)
team has developed an integrated suite of solutions for aviation, ports, borders, and critical infrastructure customers globally. We have over 24,000 products deployed in more than 120 countries, including top-tier security checkpoint and inspection systems. At Leidos, we favor innovators who think outside the box. This is a role for those who are restless, inquisitive, and always seeking to redefine what’s possible. If you thrive on pushing boundaries and envisioning future possibilities while others settle for the status quo, we'd love to hear from you.
Machine Learning Specialist
and be a pivotal part of our data science and AI initiatives. In this role, you will collaborate with talented professionals to design, build, and maintain machine learning models and pipelines. Your expertise will contribute to crafting innovative solutions that help detect prohibited concealed items on passengers or within their baggage. Our mission is to redefine automated security solutions through cutting-edge technology, and we are seeking passionate, curious, and team-oriented individuals to help us achieve this goal. Primary Responsibilities: Design, develop, test, and deploy machine learning models. Work with large datasets, focusing on cleaning, preprocessing, and feature engineering. Collaborate with cross-disciplinary teams, including data scientists, engineers, and product managers to integrate ML models into applications. Monitor model performance, retrain, and update models as necessary. Contribute to documentation and establish best practices. Stay updated on the latest research, tools, and technologies in machine learning. Occasional travel (approximately 10%) may be required, both domestically and internationally. Requirements: Bachelor's degree in Computer Science, Engineering, Mathematics, or a related field with 2+ years of experience, or a Master's degree with less than 2 years of experience. Additional work experience may substitute for a degree. Ability to obtain a Public Trust clearance (U.S. citizenship required). Solid understanding of machine learning fundamentals, including supervised and unsupervised learning, as well as model evaluation techniques. Proficiency in Python along with key ML libraries such as scikit-learn, pandas, and NumPy. Experience in object-oriented software design. Familiarity with PyTorch or similar frameworks. Experience with cloud platforms, including AWS, GCP, or Azure. Proficient in version control tools such as Git. Exposure to MLOps concepts or tools like MLflow, Docker, and CI/CD pipelines. Basic knowledge of SQL for data queries. Strong problem-solving abilities and excellent communication skills. A genuine eagerness to learn and adapt in a dynamic environment. Preferred Qualifications: Master's degree and 1-2 years of hands-on experience in machine learning or data science (including internships, research, or full-time roles). Proven experience in building, validating, and deploying machine learning models in real-world settings. Completed projects showcasing the application of ML techniques to tackle complex problems. Certifications in cloud platforms, such as Microsoft Certified: Azure AI Engineer Associate, AWS Certified Machine Learning - Specialty, or Google Cloud Professional Machine Learning Engineer. Hands-on experience with MLOps tools and workflows, notably MLflow, Docker, CI/CD pipelines, and model monitoring. Familiarity with deep learning frameworks, especially PyTorch, and the ability to develop and refine neural network models. Exposure to data engineering workflows, such as data pipeline tools (e.g., Airflow), distributed processing (e.g., Spark), and data lake architectures. Strong documentation skills with the capacity to communicate technical details effectively to both technical and non-technical audiences. Involvement in open-source ML projects, Kaggle competitions, or relevant publications is a plus. The
Leidos Security Enterprise Solutions (SES)
team has developed an integrated suite of solutions for aviation, ports, borders, and critical infrastructure customers globally. We have over 24,000 products deployed in more than 120 countries, including top-tier security checkpoint and inspection systems. At Leidos, we favor innovators who think outside the box. This is a role for those who are restless, inquisitive, and always seeking to redefine what’s possible. If you thrive on pushing boundaries and envisioning future possibilities while others settle for the status quo, we'd love to hear from you.