Space ML Engineer Intern – Data Science Focus

The Aerospace Corporation; Chantilly (VA); On-site; USD 36,000 - 41,000; Full time

Benefits offered by this job

Comprehensive benefits

Relocation assistance

Education assistance programs

Telework options

Job summary

The Aerospace Corporation in Chantilly, VA (onsite) is seeking a Machine Learning Engineer Undergrad Intern for the Data Science and Artificial Intelligence Department. The role involves developing ML experiments (NLP, CV, time series), evaluating models for scalable, mission-critical applications, and collaborating across teams to deliver features.

Applicants should be enrolled full-time in CS/CE, with a minimum 3.0 GPA, and must be able to commit 10 weeks.

Qualifications

• Pursuing full-time in an accredited CS/CE program.
• Available to work for a minimum of 10 weeks outside term.
• GPA 3.0 or higher.
• Proficiency in Python with ML libraries (PyTorch).
• Experience with Docker/Kubernetes.
• Understanding of ML/AI and software engineering concepts.
• Familiarity with MLOps tools like MLFlow and DVC.
• Unix/Linux familiarity.
• Cloud-native development or microservices knowledge.
• U.S. citizenship and ability to obtain security clearance; transcripts required.

Responsibilities

• Develop and run ML/data science experiments (NLP, CV, time series).
• Evaluate technologies and models for scalable mission-critical apps.
• Collaborate with teams to deliver features and products.
• Present results to customer stakeholders.
• Foster learning and progress within the team.

Skills

Communication

Teamwork

Organization

Adaptability

Interpersonal skills

Education

Bachelor's Degree in Computer Science or Computer Engineering or related

Tools

Python

PyTorch

Docker

Kubernetes

MLFlow

Data Version Control

Job description

The Aerospace Corporation in Chantilly, VA (onsite) is seeking a Machine Learning Engineer Undergrad Intern for the Data Science and Artificial Intelligence Department. The role involves developing ML experiments (NLP, CV, time series), evaluating models for scalable, mission-critical applications, and collaborating across teams to deliver features.

Applicants should be enrolled full-time in CS/CE, with a minimum 3.0 GPA, and must be able to commit 10 weeks.