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Internship Applied Scientist Machine Learning Jobs in Austin, TX

Apple

Applied Scientist

Austin, TX · On-site

We are currently seeking an experienced and passionate Applied Scientist, who will work on innovative products at the intersection of causal inference, statistics, and machine learning to help ...

Apple

Applied Scientist

Austin, TX

We are currently seeking an experienced and passionate Applied Scientist, who will work on innovative products at the intersection of causal inference, statistics, and machine learning to help ...

Apple

Applied Scientist

Austin, TX · On-site

$171.60K - $302.20K/yr

We are currently seeking an experienced and passionate Applied Scientist, who will work on innovative products at the intersection of causal inference, statistics, and machine learning to help ...

Avride

Machine Learning Engineer Internship

Austin, TX · On-site

About the Internship At Avride, ML Engineer Interns operate at the intersection of cutting-edge ... Science, Robotics, Machine Learning, Applied Mathematics, or a related field with an expected ...

Avride

Machine Learning Engineer Internship

Austin, TX · On-site

About the Internship At Avride, ML Engineer Interns operate at the intersection of cutting-edge ... Science, Robotics, Machine Learning, Applied Mathematics, or a related field with an expected ...

DISCO

Senior Machine Learning Scientist

Austin, TX

$97.60K - $124.40K/yr

Your Impact The Senior Machine Learning Research Scientist is a key contributor to DISCO's machine learning and AI research initiatives, leading the development of advanced algorithms and ...

DISCO

Senior Machine Learning Scientist

Austin, TX · On-site

$97.60K - $124.40K/yr

Your Impact The Senior Machine Learning Research Scientist is a key contributor to DISCO's machine learning and AI research initiatives, leading the development of advanced algorithms and ...

Apple

Machine Learning Engineer

Austin, TX · On-site

We are looking for a passionate, highly motivated, and hands-on applied Machine Learning Engineer ... scientists/analysts, and product managers, to help develop and implement machine learning ...

ExtendMyTeam

Machine Learning Engineer

Austin, TX · On-site

You'll work closely with data scientists and engineers to bring models into production, ensuring ... This is an applied engineering role -- the software you build will solve real-world problems and ...

Apple

Machine Learning Engineer

Austin, TX · On-site

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

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Internship Applied Scientist Machine Learning information

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$25.3K

$42.2K

$87.2K

How much do internship applied scientist machine learning jobs pay per year?

As of May 28, 2026, the average yearly pay for internship applied scientist machine learning in Austin, TX is $42,209.00, according to ZipRecruiter salary data. Most workers in this role earn between $32,200.00 and $45,600.00 per year, depending on experience, location, and employer.

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 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 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 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 most commonly searched types of Applied Scientist Machine Learning jobs in Austin, TX? The most popular types of Applied Scientist Machine Learning jobs in Austin, TX are:
What are popular job titles related to Internship Applied Scientist Machine Learning jobs in Austin, TX? For Internship Applied Scientist Machine Learning jobs in Austin, TX, the most frequently searched job titles are:
What job categories do people searching Internship Applied Scientist Machine Learning jobs in Austin, TX look for? The top searched job categories for Internship Applied Scientist Machine Learning jobs in Austin, TX are:
What cities near Austin, TX are hiring for Internship Applied Scientist Machine Learning jobs? Cities near Austin, TX with the most Internship Applied Scientist Machine Learning job openings:
Internship Applied Scientist Machine Learning jobs near you
Applied Scientist

Applied Scientist

Apple

Austin, TX • On-site

Full-time

Posted 23 days ago

Apple rating

8.1

Company rating: 8.1 out of 10

Based on 661 frontline employees who took The Breakroom Quiz

6th of 30 rated technology retailers

Job description

Services at Apple help hundreds of millions of customers get the most out of the devices they love through amazing apps, award-winning shows and movies, immersive music in spatial audio, world-class workouts and meditations, super fun games and more! The Services Data Science & Analytics organization is passionate about developing discerning insights and AIML solutions to help continually improve these services and accelerate growth while maintaining a strong dedication to customer privacy. ..We are currently seeking an experienced and passionate Applied Scientist, who will work on innovative products at the intersection of causal inference, statistics, and machine learning to help optimize marketing channels, via observational testing frameworks, counterfactual modeling, and lifetime value estimation. As a key member of our diverse organization, you'll have the rare and rewarding opportunity to work with datasets of unique magnitude, richness, and dedication to privacy that will frequently require novel approaches. You'll work alongside partners across Business, Marketing, Product, Finance, and Engineering daily to deliver material customer and business value.
As an Applied Scientist, you will have the responsibility of pushing the boundaries of how Causal Inference and AIML can be leveraged to better serve our customers. You will be at the forefront of designing, developing, and deploying cutting-edge Causal Inference solutions, that directly impact our products and provide a granular understanding of key marketing effectiveness. You will also be instrumental in defining the technical vision, strategy, and execution roadmap for our AIML initiatives, ensuring that we deliver high-quality, scalable, and impactful models that solve complex customer acquisition and engagement challenges. You will also be a key driver in fostering a vibrant culture of innovation, continuous learning, and collaborative problem-solving.
Master's degree in Statistics, Economics, Mathematics, Machine Learning, Computer Science, Engineering, or a related technical field3+ years of experience as an Applied Scientist, Machine Learning, or Data Scientist roleFamiliarity with a brand range of quasi-experimental Causal Inference techniques such as diff-in-diff, synthetic control method, panel analysis, regression discontinuity design, interrupted time series, and propensity score matchingHands-on experience building Marketing Mix models and validation through Matched Market testingSolid understanding of AIML technologies including Generative AIProven track record of successfully delivering complex projects from start to finishProficiency in programming languages such as Python, R, SQL, Java, or C++Experience with cloud platforms, Spark, Docker, and MLOps tools and best practicesExcellent communication, collaboration, and presentation skills with meticulous attention to detail
PhD in related fieldHands-on experience leveraging Generative AI to improve productivity and generate new insightsCurious business attitude with an ability to condense complex concepts and models into clear and concise takeaways that drive action

What Apple employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom

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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

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