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Internship Graduate Machine Learning Jobs in Texas

Apple

Machine Learning Engineer

Austin, TX · On-site

We are looking for a passionate, highly motivated, and hands-on applied Machine Learning Engineer ... Qualifications PhD or Graduate degree with research/work experience utilizing data science ...

Apple

Machine Learning Engineer

Austin, TX

$134K - $249K/yr

Engage in continuous learning and development, staying up-to-date with the latest advances in machine learning and software engineering Preferred Qualifications PhD or Graduate degree with research ...

Apple

Machine Learning Engineer

Austin, TX

$134K - $249K/yr

Engage in continuous learning and development, staying up-to-date with the latest advances in machine learning and software engineering Preferred Qualifications PhD or Graduate degree with research ...

Apple

Machine Learning Engineer

Austin, TX

$134K - $249K/yr

Engage in continuous learning and development, staying up-to-date with the latest advances in machine learning and software engineering Preferred Qualifications PhD or Graduate degree with research ...

CVS Health

Machine Learning Engineer

Irving, TX · On-site +1

$96K - $144K/yr

... internship, or thesis in each of the following: Java, Python, or Node.js; NLP (Scikit-Learn, SpaCity, Pytorch, or Spark NLP); Machine learning, statistical analysis, and predictive modeling; Machine ...

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All JobsGraduate Machine Learning JobsInternship Graduate Machine Learning JobsInternship Graduate Machine Learning Jobs in Texas

Internship Graduate Machine Learning information

What is the difference between Internship Graduate Machine Learning vs Data Analyst?

AspectInternship Graduate Machine LearningData Analyst
Required CredentialsDegree in Computer Science, Data Science, or related field; basic knowledge of programming and statisticsDegree in Statistics, Mathematics, or related field; proficiency in data visualization and analysis tools
Work EnvironmentTech companies, research labs, startups; project-based, collaborative teamsBusiness, finance, marketing sectors; focus on reporting and data interpretation
Employer & Industry UsageUsed in tech, AI, and research industries for developing machine learning modelsCommon in corporate, finance, and consulting firms for data-driven decision making

While both roles involve working with data, an Internship Graduate Machine Learning focuses on developing algorithms and models using programming skills, often in tech environments. In contrast, a Data Analyst emphasizes interpreting data, creating reports, and supporting business decisions. The roles overlap in data handling but differ in technical depth and application focus.

What are the key skills and qualifications needed to thrive as an Internship Graduate in Machine Learning, and why are they important?

To thrive as an Internship Graduate in Machine Learning, you typically need a strong background in mathematics, programming (especially Python), and familiarity with algorithms and data structures, often supported by coursework or a degree in computer science, statistics, or a related field. Hands-on experience with machine learning frameworks like TensorFlow or PyTorch, and knowledge of tools such as Jupyter Notebooks and version control systems like Git, are highly valued. Curiosity, problem-solving, teamwork, and effective communication are crucial soft skills to excel in collaborative and innovative environments. These competencies enable interns to contribute to real-world projects, adapt to fast-changing technologies, and communicate findings clearly within interdisciplinary teams.

What are Internship Graduate Machine Learning positions?

Internship Graduate Machine Learning positions are entry-level roles designed for recent graduates or students who have completed coursework in machine learning, data science, or related fields. These internships provide hands-on experience working with real-world data, building and testing machine learning models, and collaborating with experienced professionals. Interns gain exposure to industry-standard tools and techniques, helping them bridge the gap between academic learning and practical application. Such positions are valuable for building a portfolio, networking, and enhancing job prospects in the rapidly growing field of artificial intelligence.

What types of projects do Internship Graduate Machine Learning roles typically involve, and how are responsibilities structured within the team?

Internship Graduate Machine Learning roles often focus on supporting ongoing research or development projects, such as building predictive models, cleaning and analyzing data, or prototyping algorithms. Interns usually collaborate closely with data scientists and engineers, contributing to specific project milestones while learning best practices in model development and deployment. Responsibilities are often structured to allow for mentorship and feedback, with interns participating in regular team meetings, code reviews, and brainstorming sessions. This collaborative environment provides valuable exposure to real-world machine learning workflows and helps interns build both technical and soft skills relevant to the field.
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Internship Graduate Machine Learning jobs near you
Machine Learning Engineer

Machine Learning Engineer

Neuralink

Austin, TX • On-site

$199K - $331K/yr

Full-time

Medical, Dental, Vision, Retirement

Re-posted 13 days ago

Job description

About Neuralink:
We are creating devices that enable a bi-directional interface with the brain. These devices allow us to restore movement to the paralyzed, restore sight to the blind, and revolutionize how humans interact with their digital world.
About the Team:
The BCI team develops the software and systems that communicate with the brain. These systems decode raw neural signals into useful actions, such as moving a cursor, typing, or actuating a robotic arm. Additionally, real-world data, such as video feeds, can be encoded into neural data to project images into the visual cortex. We also work closely with users to gather feedback, make improvements, and fundamentally reshape the user experience and interface of the BCI.
About the Role:
Engineers on the BCI team utilize signal processing and machine learning to communicate with the brain. You will have access to the most cutting-edge neural interface hardware and develop state-of-the-art neural encoders and decoders. No prior knowledge of neuroscience is required; we value simple solutions grounded in first principles.
Neuralink designs all hardware in-house, from custom ASICs to thin-film arrays. There is no part of the technical design that cannot change. Learnings from your work will directly influence next-generation device architecture.
Job Responsibilities:
  • Telepathy Product: Develop and refine models that decode neural data, enabling individuals with paralysis to reliably type at 35 words per minute or control robotics arms for activities of daily living.
  • Blindsight Product: Formulate research questions to guide the development of neural networks and signal processing algorithms that will restore vision to those affected by blindness.
  • Utilize your fundamental understanding of neural networks and data science to develop models that serve as the foundation for machine learning applications for BCI.
  • Lead the team by performing at a high standard, setting the bar for how we build and operate our systems.
  • Inform our hardware roadmap by understanding users and identifying the product features that would have the greatest impact on their quality of life.
About You:
  • Experience writing production-level C/C++/Rust and Python
  • Proven track record of designing, building, and shipping real-time ML products
  • Strong foundation in signal processing, algorithms, and software engineering principles
  • Bachelor's degree in relevant field or equivalent experience

Fast forward to 40:32 to learn more about neural decoding:
Expected Compensation:
The anticipated base salary for this position is expected to be within the following range. Your actual base pay will be determined by your job-related skills, experience, and relevant education or training. We also believe in aligning our employees' success with the company's long-term growth. As such, in addition to base salary, Neuralink offers equity compensation (in the form of Restricted Stock Units (RSU)) for all full-time employees.
Base Salary Range:
$199,000-$331,000 USD
What We Offer:
Full-time employees are eligible for the following benefits listed below.
  • An opportunity to change the world and work with some of the smartest and most talented experts from different fields
  • Growth potential; we rapidly advance team members who have an outsized impact
  • Excellent medical, dental, and vision insurance through a PPO plan
  • Paid holidays
  • Commuter benefits
  • Meals provided
  • Equity (RSUs) *Temporary Employees & Interns excluded
  • 401(k) plan *Interns initially excluded until they work 1,000 hours
  • Parental leave *Temporary Employees & Interns excluded
  • Flexible time off *Temporary Employees & Interns excluded

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