2027 Machine Learning Engineering Graduate Intern

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 selected candidate will be required to work full-time, onsite at our facility in El Segundo, CA, Chantilly, VA or Colorado Springs, CO.

What You’ll Be Doing

• 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

What Corporate Skills You’ll Bring

• Strong written and oral communication skills

• Must work well in a team environment

• Possess organizational, time management and project management skills

• Demonstrate flexibility and ability to adapt to changing organizational need

• Interpersonal skills to coordinate efforts and work with other internal and external organizations

What You Need to be Successful

Minimum Requirements

• Currently enrolled full-time in an accredited college/university program pursuing a Master's or PhD 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 Master's or PhD degree program full-time after completion of the internship.

• Minimum GPA of 3.0

• Bachelor's degree completed by internship start date

• 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.

How You Can Stand Out

It would be impressive if you have one or more of these:

• 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

Temporary housing assistance is not available.