2026 Machine Learning Engineering Grad Intern

The Aerospace Corporation•Chantilly, VA

1d•Onsite

About The Position

The Aerospace Corporation is the trusted partner to the nation’s space programs, solving the hardest problems and providing unmatched technical expertise. As the operator of a federally funded research and development center (FFRDC), we are broadly engaged across all aspects of space— delivering innovative solutions that span satellite, launch, ground, and cyber systems for defense, civil and commercial customers. When you join our team, you’ll be part of a special collection of problem solvers, thought leaders, and innovators. Join us and take your place in space. The Aerospace Corporation is hiring a Machine Learning Engineer Intern for the Data Science and Artificial Intelligence Department (DSAID) within the Information Systems and Cyber Division (ISCD). This position will be full-time, 100% onsite at our office in Chantilly, VA. Information Systems and Cyber Division (ISCD) staff work with the latest in information system technologies, such as elastic compute clouds, containerization, microservices, real-time operating systems, and visualization frameworks, with expertise in cyber security, software architecture, software engineering, data science, Artificial Intelligence, process improvement, and software development to deliver responsive, resilient, high-performance software intensive systems to our Intelligence Community, DoD, and civilian customers. DSAID consists of a diverse team of engineers, data scientists, and programmers with a passion for researching, prototyping, understanding, and building AI and data enabled tools across the space enterprise. We are a growing, innovative, and collaborative department providing technical expertise in AI and Machine Learning to many of Aerospace’s customers, such as the Missile Defense Agency, NASA, Space Development Agency and the National Reconnaissance Office. We apply data science and AI knowledge across the space enterprise, to Aerospace enterprise capabilities, and towards corporate workforce development and strategic focus areas. Machine Learning Engineers work on teams spanning various disciplines, experience levels, and organizational boundaries. The intern will be developing and executing machine learning and data science experiments, in the domains of natural language processing, computer vision, time series analysis, reinforcement learning, etc. They will also be evaluating technologies and data science models for use in scalable and resilient mission-critical applications, collaborating with teams of various sizes to deliver features and products, presenting written and verbal results to customer stakeholders, and reinforcing an environment of learning and progress with team members and others.

Requirements

Currently enrolled full-time in an accredited college/university program pursuing a Master's Degree in Computer Science, Computer Engineering, or related discipline.
Availability to work full-time for a minimum of 10 weeks outside of university term and ability to return to a degree program full-time after completion of the internship.
Minimum GPA of 3.0
Proficiency in Python, including major ML libraries and tools (PyTorch)
Experience with container orchestration tooling (Docker, Kubernetes, etc.)
Experience with and understanding of machine learning and artificial intelligence, software engineering, and statistics
Experience with and understanding of software engineering concepts with an AI focus (MLOps/DevOps, ML Development Lifecycle, Scalable ML Architecture, etc.)
Familiarity with MLOps processes and tools (MLFlow, Data Version Control etc.)
Specific experience designing either computer vision or natural language processing applications leveraging ML models.
Experience in leveraging GPUs to scale and measure ML solution performance (NVIDIA developer tools etc.)
Familiarity with Unix/Linux operating systems
Experience with cloud native application development or cloud infrastructure, Microservice architectures
This position requires the ability to obtain and maintain a security clearance, which is issued by the U.S. government. U.S. citizenship is required to obtain a security clearance.
Transcripts required.

Nice To Haves

GPA 3.5 or higher
Active security clearance
Strong leadership skills
Familiarity with High Performance Computing hardware for ML (GPUs, TPUs), CUDA programming, and advanced ML optimization techniques and architectures
Experience with Slurm, Kubernetes or other cluster job orchestration frameworks leveraging GPU resources to run distributed ML training jobs at scale
Experience with building ML Solutions on edge and embedded hardware (ARM devices, Jetson Series, etc.)
Experience with Distributed and stream data processing, big data frameworks (Hadoop, Spark, Flink etc.)
Experience building scalable Agentic and Generative AI solutions for narrow-scoped use cases

Responsibilities

Developing and executing machine learning and data science experiments, in the domains of natural language processing, computer vision, time series analysis, reinforcement learning, etc.
Evaluating technologies and data science models for use in scalable and resilient mission-critical applications
Collaborating with teams of various sizes to deliver features and products
Presenting written and verbal results to customer stakeholders.
Reinforcing an environment of learning and progress with team members and others

Benefits

Comprehensive health care and wellness plans
Paid holidays, sick time, and vacation
Standard and alternate work schedules, including telework options
401(k) Plan — Employees receive a total company-paid benefit of 8%, 10%, or 12% of eligible compensation based on years of service and matching contributions; employees are immediately eligible and vested in the plan upon hire
Flexible spending accounts
Variable pay program for exceptional contributions
Relocation assistance
Professional growth and development programs to help advance your career
Education assistance programs
An inclusive work environment built on teamwork, flexibility, and respect