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Internship Mechanical Engineering Machine Learning Jobs in Texas

In this role, you'll be expected to perform many ML engineering activities, including one or more ... Internship experience does not apply)*** **At least 4 years of experience programming with Python ...

New

SUMMARY The Machine Learning Engineer provides hands-on expertise in designing, implementing, and scaling AI solutions, while collaborating with cross-functional teams to advance machine learning ...

In this role, you'll be expected to perform many ML engineering activities, including one or more ... Internship experience does not apply) * At least 4 years of experience programming with Python ...

New

Lead Machine Learning Engineer

Plano, TX · On-site

$98K - $129K/yr

In this role, you'll be expected to perform many ML engineering activities, including one or more ... Internship experience does not apply) * At least 4 years of experience programming with Python ...

Lead Machine Learning Engineer

Plano, TX

$98K - $129K/yr

In this role, you'll be expected to perform many ML engineering activities, including one or more ... Internship experience does not apply) * At least 4 years of experience programming with Python ...

About the Job The Varsity Tutors Live Learning Platform has thousands of students looking for ... fluid mechanics, heat transfer, machine design, manufacturing processes, and control systems.

As part of our AI team, you'll collaborate closely with engineering teams to deliver high-impact ... Contribute to our machine learning repositories and optimize models for performance, scalability ...

Showing results 41-60

Internship Mechanical Engineering Machine Learning information

What is the difference between Internship Mechanical Engineering Machine Learning vs Mechanical Engineer?

AspectInternship Mechanical Engineering Machine LearningMechanical Engineer
Required CredentialsTypically pursuing or recently completed a degree in Mechanical Engineering or related field; familiarity with machine learning toolsBachelor's degree in Mechanical Engineering; professional licensure often not required for entry-level roles
Work EnvironmentInternship setting, often in research labs or tech companies, focusing on project-based learningDesign, analysis, and manufacturing environments, including offices, factories, and labs
Employer & Industry UsageUsed by tech companies, research institutions, and engineering firms exploring AI applications in mechanical systemsWidely employed across manufacturing, automotive, aerospace, and energy sectors

In summary, an Internship Mechanical Engineering Machine Learning focuses on gaining experience at the intersection of mechanical engineering and machine learning, often in research or tech environments. A Mechanical Engineer typically works on designing and maintaining mechanical systems across various industries, with a broader scope and more established credentials.

What are the most commonly searched types of Mechanical Engineering Machine Learning jobs in Texas?

The most popular types of Mechanical Engineering Machine Learning jobs in Texas are:

What are popular job titles related to Internship Mechanical Engineering Machine Learning jobs in Texas?

For Internship Mechanical Engineering Machine Learning jobs in Texas, the most frequently searched job titles are:

What job categories do people searching Internship Mechanical Engineering Machine Learning jobs in Texas look for?

The top searched job categories for Internship Mechanical Engineering Machine Learning jobs in Texas are:

Infographic showing various Internship Mechanical Engineering Machine Learning job openings in Texas as of August 2026, with employment types broken down into 75% Full Time, and 25% Contract. Highlights an 100% In-person job distribution.

Machine Learning Engineer, Wallet Intelligence and Machine Learning

Apple

Austin, TX • On-site

Full-time

Re-posted 4 days ago


Apple rating

8.0

Company rating: 8.0 out of 10

Based on 677 frontline employees who took The Breakroom Quiz

7th of 30 rated technology retailers


Job description

Are you motivated to protect users and their accounts while delivering the best possible customer experience? Come join the Wallet Intelligence and Machine Learning team, where we help secure users' digital lives across Apple's devices without sacrificing privacy. Machine Learning Engineers here build analytical solutions and think deeply about where they fit into a larger system, staying ahead of fraud and applying the best privacy-preserving and fraud-prevention methods available to make Apple products, and especially Apple Pay and Apple Wallet, the safest platform people can use.
The On Device Insights team at Apple develops machine learning models that run directly on users' devices to protect them from fraud, holding themselves to an exceptionally high bar for privacy. As part of the Wallet Intelligence and Machine Learning team, you will help secure users' digital lives across Apple's devices - including Apple Pay and Apple Wallet - without sacrificing privacy. This is a mission-driven team that thrives on hard problems, healthy skepticism, and open collaboration.
Description
We are looking for a Machine Learning Engineer to help develop and launch on-device technologies that keep our users safe, working closely with engineering, security, program management, and business partners.
Our work is applied and pragmatic by necessity. Models must run in real time and in the background on the device without slowing down something as simple as an in-app purchase, which means designing within real constraints like model size, inference budgets, and memory. Because we often need to anticipate fraud rather than react to each new pattern as it appears, we have to be proactive and think ahead. This role is a chance to take ownership of a problem area, build a system-wide understanding of where our models fit, and apply your expertise in machine learning in an innovative and fast-moving environment.
If you're energized by ambiguity, motivated by a meaningful mission, and the kind of person who digs beneath the surface and questions your own assumptions before forming a recommendation, we'd love to hear from you.
Minimum Qualifications
Experience with machine learning methods such as classification, clustering, and anomaly detection.
Strong programming skills in one or more languages such as Python, Scala, or Java.
Experience processing and analyzing data at scale using distributed data or compute frameworks.
Ability to communicate the results of analysis clearly and succinctly to a range of audiences.
Experience delivering results on ambiguous, loosely defined problems, working with others.
Rigorous analytical thinking, including the ability to question assumptions, reason through a problem, and justify a recommendation with sound evidence.
Preferred Qualifications
Experience deploying machine learning in resource-constrained or real-time environments, such as on-device deployment, model compression, or optimizing for inference budgets.
Experience with distributed data and compute frameworks such as Spark, Ray, or Daft.
Familiarity with privacy-preserving machine learning techniques.
Background in fraud detection, risk modeling, or security-focused machine learning.
Familiarity with iOS development.
We're open to a range of specializations and are excited by candidates who bring a differentiating strength to the team, whether that's a research background, deep systems thinking, or expertise we don't yet have. Tell us what you'd add.

What Apple employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom


Apple logo

About Apple

Sourced by ZipRecruiter

Imagine what you could do here! At Apple, new ideas have a way of becoming extraordinary products, services, and customer experiences very quickly. Bring passion and dedication to your job and there's no telling what you could accomplish. Dynamic, intelligent people and inspiring, innovative technologies are the norm here. The people who work here have reinvented entire industries with all Apple Hardware products. The same real passion for innovation that goes into our products also applies to our practices strengthening our dedication to leave the world better than we found it.

Industry

Computer and electronic product manufacturing

Company size

10,000+ Employees

Headquarters location

Cupertino, CA, US

Year founded

1976