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Internship Applied Scientist Machine Learning Jobs in Texas

Machine Learning Engineer

Austin, TX · On-site

$138K/yr

Python and a modern deep learning framework , fluently, as your daily working environment. * Enough C++ to be useful. Inference runs in C++ on the vehicle. You don't need to be a C++ specialist, but ...

This role sits at the intersection of applied research, machine learning engineering, data science, and business transformation. The ideal candidate combines strong technical expertise in Large ...

This role sits at the intersection of applied research, machine learning engineering, data science, and business transformation. The ideal candidate combines strong technical expertise in Large ...

Preferred : • Advanced degree in Computer Science, Machine Learning, Robotics, or a related field. • Experience developing ML algorithms for autonomous vehicles or robotics applications. • ...

Machine Learning Engineer

Austin, TX · On-site

$138K/yr

Python and a modern deep learning framework , fluently, as your daily working environment. * Enough C++ to be useful. Inference runs in C++ on the vehicle. You don't need to be a C++ specialist, but ...

Machine Learning Engineer

Frisco, TX · On-site

$140 - $190/hr

D. preferred) in Computer Science, Machine Learning, or a closely related field. * Extensive knowledge of computer vision architectures such as Vision Transformers and VLMs along with OpenCV and PIL.

The Senior Machine Learning Scientist develops advanced algorithms and models to extract valuable insights from complex data sets. This role combines deep technical expertise in machine learning with ...

The Senior Machine Learning Scientist develops advanced algorithms and models to extract valuable insights from complex data sets. This role combines deep technical expertise in machine learning with ...

Showing results 21-40

Internship Applied Scientist Machine Learning information

What types of projects do internship applied scientists in machine learning typically work on, and how do they contribute to the team's goals?

Internship Applied Scientists in Machine Learning often collaborate with multidisciplinary teams to tackle real-world problems using data-driven approaches. Typical projects might include developing and fine-tuning machine learning models, conducting experiments to validate hypotheses, or assisting in the deployment of algorithms into production systems. Interns are expected to contribute fresh perspectives, help with data preprocessing, and perform thorough model evaluations. Through these projects, interns gain hands-on experience while directly supporting the team's research and product development objectives.

What is the difference between Internship Applied Scientist Machine Learning vs Internship Data Scientist?

AspectInternship Applied Scientist Machine LearningInternship Data Scientist
Required CredentialsRelevant degrees in Computer Science, Data Science, or related fields; knowledge of ML frameworksDegrees in Statistics, Data Science, or related fields; strong analytical skills
Work EnvironmentResearch and development teams, focus on ML model developmentBusiness teams, focus on data analysis and insights
Employer & Industry UsageTech companies, AI-focused organizationsVarious industries including tech, finance, healthcare
Comparison Search IntentUnderstanding roles in ML research and developmentUnderstanding data analysis and business insights roles

Internship Applied Scientist Machine Learning roles focus on developing and applying machine learning models, often in research settings. In contrast, Internship Data Scientist positions emphasize analyzing data to generate insights for business decisions. Both roles require strong analytical skills and relevant educational backgrounds, but they differ in their primary focus and work environment.

What are the key skills and qualifications needed to thrive as an internship applied scientist in machine learning, and why are they important?

To thrive as an Internship Applied Scientist in Machine Learning, you need a solid background in mathematics, statistics, and computer science, often supported by coursework or research experience in machine learning and data analysis. Familiarity with tools such as Python, TensorFlow, PyTorch, and experience working with large datasets are highly valued, along with knowledge of version control systems like Git. Strong problem-solving skills, curiosity, and the ability to communicate complex concepts clearly set top candidates apart. These competencies are crucial for effectively designing, implementing, and presenting machine learning solutions that address real-world challenges.

What does an internship applied scientist in machine learning do?

An Internship Applied Scientist in Machine Learning works on real-world projects involving the design, development, and evaluation of machine learning models and algorithms. Their responsibilities typically include data analysis, building predictive models, experimenting with new techniques, and collaborating with engineers and researchers to solve complex problems. Interns gain hands-on experience with tools like Python, TensorFlow, or PyTorch, and contribute to advancing the company's AI capabilities. The role requires a strong foundation in mathematics, statistics, and computer science, as well as the ability to communicate findings to both technical and non-technical stakeholders.
What are the most commonly searched types of Applied Scientist Machine Learning jobs in Texas? The most popular types of Applied Scientist Machine Learning jobs in Texas are:
What are popular job titles related to Internship Applied Scientist Machine Learning jobs in Texas? For Internship Applied Scientist Machine Learning jobs in Texas, the most frequently searched job titles are:
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What cities in Texas are hiring for Internship Applied Scientist Machine Learning jobs? Cities in Texas with the most Internship Applied Scientist Machine Learning job openings:

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