
Engineering Intern - Crucible Synthetic NEI (Summer 2027)
Millennial Software Solutions · Chantilly, VA
Mixed hiring record · median 51 days open
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Actively hiring
Posted 2 days ago · still listed on the employer's own board · How we score
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- 38% of this employer's openings are over 60 days old
In its favour
- Posted 2 days ago
- Still listed on the employer's own board
- Publishes a salary range
About Millennial Software
Millennial Software, part of Expedition Technology, is revolutionizing the landscape of security and defense by leveraging our core competencies in software development, automation, DevSecOps, and machine learning.
Job Description
Clearance Level Must Currently Possess
None required to start. Must be a U.S. citizen able to obtain and maintain a DoD security clearance.
Millennial Software is seeking two Engineering Interns for Summer 2027 (May 17 – August 6) at our Chantilly, VA headquarters to work on Crucible, our agentic modeling and simulation platform. Component identification models stall because real non-Earth imagery (NEI) is scarce and classified.
This project builds the data
a synthetic NEI generator that renders spacecraft from open 3D models under varied pose, lighting, range, and sensor conditions, emitting a per-component segmentation mask with every frame so labeling costs nothing.
The generator is the primary deliverable and is complete by week six. The stretch goal is to fine-tune a segmentation model on the synthetic dataset in Keystone and map predicted components (bus, solar arrays, antennas, thrusters, apertures) into a populated Target Model Database (TMDB) record. All work is unclassified using publicly available models. You will be paired with mentors, work in daily standups, and present a recorded demonstration and readout to leadership.
Essential Functions
- Build a rendering module in Crucible using open 3D spacecraft models and a parametric scene generator (orbit geometry, target pose, illumination and self-shadowing, sensor range and resolution, noise and blur)
- Emit per-component segmentation masks with every rendered frame; record rendering parameters per frame so any image can be regenerated
- Produce a labeled dataset of several thousand frames across multiple targets; demonstrate dataset generation for a new target in under one working day
- Stretch: fine-tune a segmentation model from a published architecture, run training and evaluation in Keystone against a held-out synthetic set
- Stretch: post-process predicted components into TMDB schema fields and populate one record end to end
- Document the pipeline and present at the leadership readout
Required Qualifications
- U.S. citizen able to obtain and maintain a DoD security clearance
- Rising senior (or exceptional rising junior) pursuing a BS in Computer Science, Aerospace Engineering, or related field; meets GPA requirement
- Strong Python; comfort with Git and Linux development environments
- Coursework or project experience in at least one of: computer graphics or 3D rendering, computer vision, or machine learning (PyTorch or similar)
- Available full time, on site in Chantilly, VA, for the 12-week program
Nice to Have
- Experience with rendering tools or engines (Blender, Unity, Unreal, Three.js, PyRender) or mesh formats (glTF, OBJ, STL)
- Image segmentation or object detection experience (U-Net, Mask R-CNN, SAM)
- Orbital mechanics or spacecraft systems coursework
- GPU training experience; familiarity with experiment tracking
Program Details
- Dates: May 17 – August 6, 2027 (12 weeks, full time, on site in Chantilly, VA with remote flexibility)
- Mentorship: assigned primary and backup mentor; daily standups; bi-weekly sprint planning and demos; 30/60-day checkpoints, mid-summer and final reviews
- Evaluation rubric: code quality, documentation, teamwork, communication, initiative, impact
- Final deliverable: recorded pipeline run and leadership readout; all targets set by the mentor team
Millennial Software Solutions Inc. is an Equal Opportunity Employer and does not discriminate in employment on the basis of race, color, religion, sex, national origin, political affiliation, sexual orientation, gender identity, marital status, disability and genetic information, age, membership in an employee organization, or other non-merit factor
Skills
- Machine Learning
- Python
- Git
- Linux
- Computer Vision
- PyTorch
- Unity
- Three.js
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