Machine Learning Engineering Graduate Intern

The Aerospace Corporation

Machine learning graduate intern developing experiments and scalable AI solutions for Aerospace Corporation’s defense, civil, and commercial space programs. Applying Python, deep learning, MLOps, and cloud technologies onsite.

Posted 9/10/2026internshipEl Segundo • California, Colorado • 🇺🇸 United StatesEntry Level💰 $32 - $38 per hourWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in Machine Learning, Natural Language Processing, and Computer Vision, with proficiency in Python and major ML libraries. Capable of collaborating within multidisciplinary teams and presenting complex results to stakeholders.

Highest-signal resume keywords

Proficiency In PythonExperience With PyTorchFamiliarity With Docker And KubernetesExperience With MLOps ProcessesExperience With Cloud Native Application Development

ATS Keywords

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Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills

Machine LearningNatural Language ProcessingComputer VisionReinforcement LearningStatisticsSoftware EngineeringML Development LifecycleScalable ML ArchitectureHigh-Performance ComputingCUDA Programming

Soft Skills

CollaborationCommunicationTeamworkPresentation SkillsLearning Mindset

Tools & Technologies

MLFlowData Version ControlNVIDIA Developer ToolsHadoopSparkFlinkSlurm

Industry Keywords

Cloud InfrastructureMicroservice ArchitecturesDistributed Data ProcessingBig Data FrameworksSecurity Clearance

Tech Stack

Tools & technologies

CloudDockerHadoopKubernetesLinuxPythonPyTorchSparkUnix

About the role

Key responsibilities & impact

Develop and execute machine learning and data science experiments in natural language processing, computer vision, time series analysis, reinforcement learning, and related domains
Evaluate technologies and data science models for scalable and resilient mission-critical applications
Collaborate with teams of various sizes to deliver features and products
Present written and verbal results to customer stakeholders
Reinforce an environment of learning and progress with team members and others
Work as part of multidisciplinary teams spanning experience levels and organizational boundaries

Requirements

What you’ll need

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 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 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 and microservice architectures
Ability to obtain and maintain a U.S. government-issued security clearance
U.S. citizenship required to obtain a security clearance
Transcripts required
GPA 3.5 or higher (impressive qualification)
Active security clearance (impressive qualification)
Familiarity with high-performance computing hardware for ML, CUDA programming, and advanced ML optimization techniques and architectures (impressive qualification)
Experience with Slurm, Kubernetes, or other cluster job orchestration frameworks leveraging GPU resources to run distributed ML training jobs at scale (impressive qualification)
Experience building ML solutions on edge and embedded hardware (impressive qualification)
Experience with distributed and stream data processing and big data frameworks such as Hadoop, Spark, or Flink (impressive qualification)
Experience building scalable agentic and generative AI solutions for narrow-scoped use cases (impressive qualification)

Benefits

Comp & perks

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