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SRC

engineering opportunity

Machine Learning Engineer (Intern - Summer 2027)

Develop and apply machine learning models for cloud and edge platforms while assisting with algorithm integration into hardware and software. Collaborate with subject matter experts to identify model requirements and manage data set generation and augmentation.

Fairborn, Ohio, United StatesonsiteINTERN

Posted

About the role

What will you do at SRC?

SRC, Inc. is currently seeking summer 2027 Machine Learning Engineering interns for our Dayton, OH or Syracuse, NY locations who enjoy solving interesting problems using ML. Are you excited about machine learning (ML) and want to do something meaningful? Do you want your work to make a real difference and save lives?

Our products protect our soldiers, our nation, and our allies. We solve the kinds of problems search engines don’t have answers for. Selected candidates will have the opportunity to work in small teams designing and developing solutions using deep learning and statistical methods on a variety of challenging problems.

Because of the diverse nature of our work, we can accommodate team members with varying technical backgrounds.

What You'll Do

  • Develop and apply ML models to run on both cloud hosts and edge platforms.
  • Assist with algorithm and model development and integration into hardware and software components
  • Assist with the collection, generation, and augmentation of data sets
  • Work with domain subject matter experts to identify algorithm and model requirements

What You'll Bring

  • One or more years of college with some familiarity with ML, deep reinforcement learning (DRL), or large language models (LLMs)
  • A minimum grade point average of 3.3, Most recent transcripts are required with application (unofficial transcripts are acceptable)
  • Must be able to work up to 40 hours a week
  • Strong interpersonal and communication skills
  • Ways to Stand Out
  • Experience using machine learning frameworks such as Tensorflow or Pytorch
  • Experience with prompt engineering or retrieval augmented generation (RAG) to optimize performance of LLMs
  • Experience with Python or MATLAB
  • What Sets Us Apart?
  • SRC, Inc., a not-for-profit research and development company, combines information, science, technology and ingenuity to solve “impossible” problems in the areas of defense, environment and intelligence. Across our family of companies, we apply bright minds, fresh thinking and relentless determination to deliver innovative products and services that are redefining possible®. When you join our team, you’ll be a part of something truly meaningful — helping to keep America and its allies safe and strong. You’ll collaborate with more than 1,400 engineers, scientists and professionals — with 20 percent of those employees having served in the military — in a highly innovative, inclusive and equitable work environment. You’ll receive a competitive salary and comprehensive benefits package that includes four or more weeks of paid time off to start, 10 percent employer contribution toward retirement, and 100 percent tuition support.
  • Total compensation for this role is market competitive. The anticipated range for this position based out of Syracuse, NY or Dayton, OH is estimated at $22.00 to $26.00/hour. The actual salary will vary based on applicant’s experience, skills, and abilities, geographic location as well as other business and organizational needs. SRC offers competitive benefit options, for more details please visit our website.

Which skills does this role require?

Machine learningDeep learningStatistical methodsDeep reinforcement learningLarge language modelsTensorflowPytorchPrompt engineeringRetrieval augmented generationPythonMATLABData augmentationAlgorithm developmentCloud computingEdge platformsMachine LearningDeep LearningStatistical MethodsDeep Reinforcement LearningLarge Language ModelsPrompt EngineeringRetrieval Augmented GenerationCloudEdge PlatformsData SetsAlgorithm DevelopmentDefenseIntelligenceResearch and DevelopmentPyTorchTensorFlowLLMs

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