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Machine Learning Intern - Kiewit Data Services (Summer 2027)

Kiewit

Omaha, NEFull-time / TemporarySeen 1 day agoSeen in employer's feed 1 day ago

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At a glance

Compensation
No compensation found
Location
Omaha, NE
Role Type
Internship
Schedule
Full-time / Temporary
Work Authorization
Not specified

Olive lists jobs from US employers, including remote roles you can work from the United States.

Job overview

The Machine Learning Intern will join Kiewit Data Services for a summer internship applying machine learning to construction challenges. The intern will work with operational data and a team developing AI-assisted workflow automations, improving project estimates, and building models and applications using data from job-site equipment and sensors. Expected projects include financial and schedule estimation and forward-looking modeling for robotics and instrumented job sites.

Skills & qualifications

RequiredNice to have

Skills

Analytical Skills, requiredProblem Solving, requiredMachine Learning, requiredSoftware Development, nice to havePython, nice to haveAI Tools, nice to haveWritten Communication, requiredVerbal Communication, requiredTeamwork, requiredInitiative, requiredAttention to Detail, requiredIndependent Work, required

Qualifications

Undergraduate or Graduate Degree in Listed Fields, requiredPrior Internship Experience, nice to have

Benefits

Medical Insurance
Dental Insurance
Vision Insurance
401(k) Match
Paid Time Off

Full job description

Requisition ID: 183070

Job Level: Internship

Home District/Group: DHO Kiewit Data Services

Department: Data Services

Market: Corporate Home Office

Employment Type: Full Time Temporary

Position Overview

Join Kiewit Data Services for a summer internship applying machine learning to construction challenges. You’ll work with a team building AI-assisted workflow automations, improving project estimates, and developing models and applications that use data from ground robots, drones, fixed cameras, and connected vehicles.

Projects this summer are expected to include financial and schedule estimation, along with forward-looking modeling for robotics and instrumented job sites. You’ll have the chance to work with real operational data and help turn promising ideas into tools that project teams can use.

District Overview

Kiewit Data Services helps teams across Kiewit collect, organize, and use the data behind better project decisions. Our machine learning group builds on that foundation to improve estimating, identify financial and schedule risks earlier, and draw useful insights from equipment and job-site activity. The goal is to help Kiewit plan work more accurately and reduce losses on projects.

Location

This position is based at our office at 12312 Port Grace Blvd, La Vista, NE 68128. It is not a remote or hybrid opportunity.

Responsibilities

  • Work with machine learning specialists, engineers, and project teams to understand needs and develop practical solutions.

  • Help prepare and assess data used in machine learning models and estimation tools.

  • Contribute to AI-assisted workflow automations and models that support financial and schedule estimates.

  • Explore data from robots, drones, cameras, and connected vehicles to identify patterns and support forward-looking models.

  • Investigate issues, test approaches, and explain findings to technical and nontechnical teammates.

Qualifications

  • Currently pursuing an undergraduate or graduate degree in Machine Learning, Robotics, Autonomy, Applied Mathematics, Data Analytics, a relevant Engineering field, or a related discipline.

  • Available to work full-time during the summer, approximately May through August.

  • Strong analytical and problem-solving skills, with an interest in applying machine learning to real-world data.

  • Experience building software is valued, particularly experience with Python. We also value candidates who use AI tools thoughtfully in their development work.

  • Strong written and verbal communication skills and the ability to work well with a team.

  • Initiative, attention to detail, and the ability to work independently when needed.

  • Prior internship experience is preferred but not required.

  • Commitment to safety, ethics, and high-quality work.

Other Requirements:

  • Regular, reliable attendance

  • Work productively and meet deadlines timely

  • Communicate and interact effectively and professionally with supervisors, employees, and others individually or in a team environment.

  • Perform work safely and effectively. Understand and follow oral and written instructions, including warning signs, equipment use, and other policies.

  • Work during normal operating hours to organize and complete work within given deadlines. Work overtime and weekends as required.

We offer our fulltime staff employees a comprehensive benefits package that’s among the best in our industry, including top-tier medical, dental and vision plans covering eligible employees and dependents, voluntary wellness and employee assistance programs, life insurance, disability, retirement plans with matching, and generous paid time off.

Equal Opportunity Employer, including disability and protected veteran status.

Company: Kiewit

How this job compares

Set against the 1,864 open Machine Learning jobs on Olive Jobs, counted November 11, 2026.

Pay
  • This postingNot listed
  • US median$150–241K/yr1,397 salary ranges
  • US median$35–51/hr81 hourly ranges
Openings
Olive Jobs lists 1,864 open Machine Learning jobs across the US. 9% of them nationwide are listed as remote or flexible.
Hiring the most across the US
Experience
Machine Learning postings that state a minimum ask for 5 years of experience at the median; the middle half ask for 3 to 8 years (1,338 postings).
Education
673 of the 1,864 open Machine Learning jobs (36%) ask for a bachelor's degree or higher.

Pay, requirements and demand for Intern jobs

Counted across the open, public US postings on Olive Jobs on November 11, 2026. Pay medians are the middle values of the low ends and of the high ends of postings that list both ends of a range in the same cadence (a yearly salary or an hourly rate); a range's midpoint is halfway between its ends. Pay and experience figures resting on fewer than 20 postings are left out.

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