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Graduate/PhD Research Intern, Machine Learning

Constellation Space · On-site

This listing is no longer verified as available.

MeritLog keeps this source-backed description for reference. Availability is not verified, and there is no application link here.

Last seen by MeritLog September 8, 2026Source: AshbySource version: ashby-public-job-posting-v1

Source: the employer's Ashby job board. Open the original listing for current details. Availability is not verified for this retained page.

Job details

Work model
On-site
Salary
Not listed by source
Location
Seattle

What the role asks for

What you'd do

  • Conduct independent research to design and train novel machine learning architectures.
  • Analyze massive datasets derived from flight telemetry and satellite sensors.
  • Prototyping and testing algorithms in simulated aerospace environments.
  • Publish internal papers and present findings to the core engineering team.

What they're asking for

  • Currently pursuing a Master's or Ph.D. in Computer Science, Aerospace Engineering, Mathematics, or a related field.Education
  • Strong theoretical understanding of deep learning, computer vision, or reinforcement learning.Skill
  • Proficiency in Python and standard ML frameworks (PyTorch, TensorFlow, or JAX).Skill
  • Ability to work on-site in Seattle for the duration of the internship.Skill

Parsed by MeritLog from the employer’s own posting. The full description follows below.

Job description

The Role Constellation is seeking an ambitious Graduate or PhD Research Intern to join our Data Science / AI team. You will research and develop cutting-edge machine learning models to solve complex aerospace challenges, from predictive maintenance to autonomous orbital navigation. Responsibilities - Conduct independent research to design and train novel machine learning architectures. - Analyze massive datasets derived from flight telemetry and satellite sensors. - Prototyping and testing algorithms in simulated aerospace environments. - Publish internal papers and present findings to the core engineering team. Requirements - Currently pursuing a Master's or Ph.D. in Computer Science, Aerospace Engineering, Mathematics, or a related field. - Strong theoretical understanding of deep learning, computer vision, or reinforcement learning. - Proficiency in Python and standard ML frameworks (PyTorch, TensorFlow, or JAX). - Ability to work on-site in Seattle for the duration of the internship.

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