You are viewing a preview of this job. Log in or register to view more details about this job.

Research & Innovation Support Intern

MxV Rail
Email

Posting Date: 09/01/2026                                           Closing Date: 10/31/2026

 

Research & Innovation Support Intern

 

Overview:

The internship will support the Association of American Railroads (AAR) Strategic Research Initiative (SRI) inspection program, particularly rail and wheel inspection projects. 

 

Projects:

  • Rail Inspection
  • Machine learning on raw time-series ultrasonic data (A-scans)
  • Integrate an edge computing device with ultrasonic hardware/software for real-time A-scan analysis and processing
  • Develop time-series ultrasonic and electromagnetic data fusion approach for rolling contact fatigue (RCF) characterization in rails
  • Demonstration of developed approach/methodology
  • Wheel Inspection
  • Wheel sub-surface fatigue crack (SSFC) growth monitoring using a multi-sensor data fusion approach
  • Develop data fusion methodology
  • Demonstrate the developed approach/ methodology

 

Preferred Level of Education: 

  • M.S. or Ph.D. students in the Engineering field or computer Science/ Data Science.

 

About MxV Rail:

Located near the foot of the beautiful Rocky Mountain Front Range, MxV Rail is the world’s premier rail advisory because we have the expertise to keep our industry moving forward. Toward safer equipment and people. More transformative technology. Toward more efficient operations and fewer emissions. We are called MxV Rail because it is the formula for momentum, and that’s what we deliver. We advance our industry, our clients, and the best ideas. We help set the standards and solve immediate and long-standing challenges. We put breakthrough technologies to the test, and train first responders how to do things right when things go wrong. In partnership, we safely experiment, learn, adapt, and advance, so our clients can thrive.

 

Primary Responsibilities:

  • Data Preprocessing: Clean, normalize, and annotate large inspection datasets (e.g., images, time-series signals).
  • Data Fusion Implementation: Develop algorithms (e.g., Kalman filters, deep learning architectures) that merge data from multiple inspection sensors to improve defect detection accuracy.
  • Model Training: Build and train machine learning models (CNNs, RNNs, or Transformers) using frameworks like PyTorch or TensorFlow to classify flaws or predict material fatigue.
  • Edge Optimization: Deploy, quantize, and compress trained AI/ML models to run efficiently on low-power, localized edge devices (e.g., embedded systems, IoT sensors).
  • Testing & Validation: Validate model outputs using statistical bounds and Probability of Detection (POD) studies.
  • Ensure that all duties and responsibilities are performed in a safe manner.
  • Perform other related duties as assigned.

 

Required Skills & Abilities:

  • Open to learning and living the MxV Rail values (Momentum, Insight, Teamwork, Rigor, Purpose) in all facets of the organization'swork.
  • Bachelor’s degree in mechanical engineering, Civil Engineering, Electrical Engineering, Computer Science, Data Science, or a related field. 
  • Knowledge of non-destructive testing (NDT) and non-destructive evaluation (NDE) principles and methodologies. 
  • Understanding of signal processing concepts and techniques.
  • Academic or practical experience with artificial intelligence (AI) and machine learning (ML) applications.
  • Must be proficient in coding.
  • MxV Rail policy requires all prospective employees to complete and pass a criminal background check (Disclosure for Consumer Reports Consent Form) and a pre-employment substance abuse screening (Applicant Consent for Drug Testing Form) as a condition of employment. 

 

Preferred Qualifications: 

  • Programming Skills: Expert proficiency in Python (for ML modeling) and familiarity with C/C++ (for hardware and edge integration).
  • AI/ML Toolkits: Hands-on experience with core ML libraries and frameworks such as PyTorch, TensorFlow, or Scikit-Learn.
  • Domain Knowledge: Foundational understanding of signal processing, wave mechanics, or structural materials.
  • Edge/Embedded Concepts: Familiarity with deploying models onto embedded platforms (e.g., NVIDIA Jetson, Raspberry Pi) or knowledge of quantization, pruning, and model optimization is highly preferred.

 

Length of Service: 

  • Must be available to work from mid-May through the end of August.

 

Working Environment and Level of Physical Activity:

The conditions herein are representative of those that must be met by an employee to successfully perform the essential functions of this job. Reasonable accommodation may be made to enable individuals with disabilities to perform essential job functions.

  • Environment: Office and field environments. Must be able to walk in an industrial and/or railroad environment, including uneven surfaces such as ballast.
  • Vision: See in the normal visual range with or without correction; vision sufficient to read computer screens and printed documents.
  • Hearing: Hear in the normal audio range with or without correction.

 

Benefits Overview:

  • Railroad Retirement
  • 401(k) Program with Company Match 
  • Fortnight Schedule
  • Paid Holidays

 

Hourly Rate: $20

 

Commitment to Non-Discrimination. All qualified applicants will receive consideration for employment without regard to disability, status as a protected veteran, or any other status protected by applicable federal, state, or local law.