Machine Learning Engineer Intern

Key Skills

Feature Extraction, Model Selection, Python Programming, PyTorch, Scikit-learn, Supervised learning, TensorFlow, Unsupervised learning

Job Description

Company Overview: SAIC is a premier technology integrator solving our nation's most complex modernization and readiness challenges across the defense, space, federal civilian, and intelligence markets. Our robust portfolio of offerings includes high-end solutions in systems engineering and integration, enterprise IT, cyber security, AI/ML, and data analytics.

*This is a part-time remote job that can be worked anywhere within the U.S.*

 Key Responsibilities:

• Collaborate with cross-functional teams to understand business requirements and translate them into technical solutions that leverage machine learning and data science techniques.
• Assist in the development and deployment of machine learning models, algorithms, and data pipelines to solve complex problems and optimize processes.
• Conduct data preprocessing, feature engineering, and exploratory data analysis to enhance model performance and insights.
• Participate in designing and implementing experiments to evaluate model performance and iterate on improvements.
• Assist in the integration of machine learning solutions into production systems, ensuring scalability, robustness, and reliability.
• Stay up-to-date with the latest advancements in machine learning, artificial intelligence, and data science to propose innovative ideas and techniques for improving existing systems.
• Contribute to documentation, knowledge sharing, and training to ensure the transfer of technical knowledge within the team.

Qualifications:

• Must be a US Citizen.
• Currently enrolled in an accredited university focusing in Computer Science, Engineering, Mathematics, or a related field. 
• Strong foundation in machine learning concepts and techniques, including supervised and unsupervised learning, feature selection, and model evaluation.
• Proficiency in programming languages such as Python, and experience with machine learning libraries (e.g., TensorFlow, PyTorch, scikit-learn).
• Familiarity with data preprocessing, cleaning, and transformation techniques to handle real-world data challenges.
• Basic understanding of statistics and experimental design for evaluating model performance and making data-driven decisions.
• Exposure to version control systems (e.g., Git) and collaborative coding practices.
• Strong problem-solving skills and the ability to work effectively in a team-oriented, fast-paced environment.
• Excellent communication skills to convey complex technical concepts to non-technical stakeholders.
• Previous coursework, projects, or internships in machine learning or data science is a plus.
• Any experience with cloud platforms (e.g., AWS, Azure, GCP) and big data technologies is advantageous.

SAIC accepts applications on an ongoing basis and there is no deadline.

Covid Policy: SAIC does not require COVID-19 vaccinations or boosters. Customer site vaccination requirements must be followed when work is performed at a customer site.