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Internship Applied Scientist Machine Learning Jobs

Strayos

$13 - $17.50/hr

... Applied Scientist internship opportunity ... Here at Strayos, we use advanced computer vision and machine learning on images and machine sensors ...

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 ...

Amazon

Applied Scientist

Seattle, WA · On-site

Are you a MS or PhD student interested in a 2024 Applied Science Internship in the fields of Speech, Robotics, Computer Vision, or Machine Learning/Deep Learning? Do you enjoy diving deep into hard ...

Amazon

Applied Scientist

Seattle, WA

Are you a MS or PhD student interested in a 2024 Applied Science Internship in the fields of Speech, Robotics, Computer Vision, or Machine Learning/Deep Learning? Do you enjoy diving deep into hard ...

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 ...

Ramp

Senior Applied Scientist, Credit Risk

New York, NY · Remote

$165.80K - $228K/yr

You'll work at the intersection of machine learning, statistics, economics, and product strategy ... Applied scientists at Ramp focus on solving quantitative problems across credit, fraud, growth, and ...

Ramp

Senior Applied Scientist, Credit Risk

New York, NY · On-site

$165.80K - $228K/yr

You'll work at the intersection of machine learning, statistics, economics, and product strategy ... Applied scientists at Ramp focus on solving quantitative problems across credit, fraud, growth, and ...

Grid

Applied Scientist

Seattle, WA

$120K - $200K/yr

Proven experience in Machine Learning and/or Applied Science, including a strong background in statistical inference, machine learning. This is a requirement, a bachelors or master's degree in ...

Grid

Applied Scientist

Seattle, WA

$120K - $200K/yr

Proven experience in Machine Learning and/or Applied Science, including a strong background in statistical inference, machine learning. This is a requirement, a bachelors or master's degree in ...

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 ...

Fuze Health

OR · On-site

As a Applied Scientist, you will lead the end-to-end development of advanced machine learning solutions, guiding initiatives from ideation through production, and mentoring peers across the ...

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Internship Applied Scientist Machine Learning information

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$25.5K

$42.6K

$88K

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 the United States is $42,584.00, according to ZipRecruiter salary data. Most workers in this role earn between $32,500.00 and $46,000.00 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.

More about Internship Applied Scientist Machine Learning jobs
What cities are hiring for Internship Applied Scientist Machine Learning jobs? Cities with the most Internship Applied Scientist Machine Learning job openings:
What are the most commonly searched types of Applied Scientist Machine Learning jobs? The most popular types of Applied Scientist Machine Learning jobs are:
What states have the most Internship Applied Scientist Machine Learning jobs? States with the most job openings for Internship Applied Scientist Machine Learning jobs include:
What job categories do people searching Internship Applied Scientist Machine Learning jobs look for? The top searched job categories for Internship Applied Scientist Machine Learning jobs are:
Internship Applied Scientist Machine Learning jobs near you
Infographic showing various Internship Applied Scientist Machine Learning job openings in the United States as of May 2026, with employment types broken down into 1% As Needed, 87% Full Time, 11% Part Time, and 1% Contract. Highlights an 92% Physical, 1% Hybrid, and 7% Remote job distribution, with an average salary of $42,584 per year, or $20.5 per hour.
Senior Applied Scientist, Machine Learning

Senior Applied Scientist, Machine Learning

McAfee Corp.

Reston, VA • On-site

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 13 days ago

Job description

Job Title:
Senior Applied Scientist, Machine Learning
Role Overview:
We are seeking a Senior Applied Scientist to join McAfee's Consumer ML team and drive AI-powered solutions that deliver personalized experiences, optimize pricing, and improve payment success for millions of global customers. In this role, you will lead the end-to-end development and deployment of high-impact ML models across fraud detection, dynamic pricing, journey optimization, and contextual recommendation systems. You'll design and execute experimentation frameworks, champion GenAI tooling adoption to accelerate development, and apply advanced techniques, including deep learning and reinforcement learning.
This is a hands-on technical leadership role requiring 8+ years of Applied ML experience, proven expertise in personalization, pricing optimization, or churn/propensity modeling for digital subscriptions, and strong cross-functional collaboration skills to translate ML innovation into measurable business outcomes.
This is a hybrid position located in the United States but you will be required to be onsite on an as needed basis. When you are not working onsite you will work from your home office.
About the Role
  • Strategic Vision: Drive the ML science strategy for pricing, recommendation systems, and personalized consumer experiences, to maximize McAfee's customer value.
  • Model Development: Lead the research, implementation, and delivery of Applied AI/ML models using user behavior and subscription data to enhance personalization and product value.
  • Optimization & Experimentation: Lead algorithm development to optimize consumer journeys, increase conversion rates, and drive monetization strategies. Design and execute controlled experiments (A/B and multivariate tests) to validate and enhance model performance.
  • Generative AI Enablement: Leverage GenAI tools-such as GitHub Copilot, Claude Code, and other AI coding assistants-to amplify development productivity in data preparation, model tuning, and orchestration workflows. Champion the integration of GenAI capabilities into the ML lifecycle to accelerate experimentation and reduce time-to-market.
  • Research & Knowledge Sharing: Stay at the forefront of ML science, contributing to the development of new algorithms and applications. Share knowledge through internal presentations, publications, and participation in academic or industry forums.
  • Reinforcement Learning is a Plus: Guide the team in applying reinforcement learning methods such as contextual bandits, SARSA, and Q-learning. Implement exploration-exploitation strategies, including epsilon-greedy, Thompson sampling, and Upper Confidence Bound (UCB) to optimize decision-making for pricing and recommendation engines.
  • Cross-Functional Collaboration: Partner with Marketing, Product, Sales, and Engineering teams to ensure ML solutions align with strategic objectives and deliver measurable business impact.

About You
  • Experience: 8+ years of expertise in Applied AI & ML, complemented by at least 3 years of technical leadership experience mentoring machine learning scientists in technical capacities.
  • Mandatory Qualification: Proven track record in at least one of the following: implementing AI/ML-based personalized messaging techniques to enhance consumer/customer product experiences; developing AI/ML-based dynamic pricing and personalized offer strategies for pricing optimization; or creating customer/consumer churn and propensity models specifically for digital subscription use cases
  • Technical Expertise: Deep proficiency in classical ML and deep learning techniques (e.g., XGBoost, Random Forest, SVMs, deep neural networks), autoencoders, representation learning, and deep recommender system techniques, as well as reinforcement learning methods (contextual bandits, SARSA, Q-learning). Strong programming skills in Python, SQL, and ML frameworks.
  • Tooling & Libraries: Proficient with ML libraries such as PyTorch and Scikit-learn, with a strong background in feature engineering, model validation, and evaluation metrics.
  • Mathematical Foundations: Solid understanding of the mathematical and statistical principles underpinning ML algorithms (linear algebra, calculus, probability) and a passion for solving complex problems through research and application of emerging techniques.
  • Communication & Collaboration: Excellent communicator who can distill complex ML concepts for both technical and non-technical stakeholders and collaborate effectively across cross-functional teams to align ML models with business goals.

#LI-Hybrid
Company Overview
McAfee is a leader in personal security for consumers. Focused on protecting people, not just devices, McAfee consumer solutions adapt to users' needs in an always online world, empowering them to live securely through integrated, intuitive solutions that protects their families and communities with the right security at the right moment.
Company Benefits and Perks:
We work hard to embrace diversity and inclusion and encourage everyone at McAfee to bring their authentic selves to work every day. We offer a variety of social programs, flexible work hours and family-friendly benefits to all of our employees.
  • Bonus Program
  • 401k Retirement Plan
  • Medical, Dental, Vision, Basic Life, Short Term Disability and Long-Term Disability Coverage
  • Paid Parental Leave
  • Support for Community Involvement
  • 14 Paid Company Holidays
  • Unlimited Paid Time Off for Exempt Employees
  • 96 Hours of Sick Time and 120 Hours of Vacation for Non-Exempt Employees Accrued Each Year

We're serious about our commitment to diversity which is why McAfee prohibits discrimination based on race, color, religion, gender, national origin, age, disability, veteran status, marital status, pregnancy, gender expression or identity, sexual orientation or any other legally protected status.
The starting pay range for this position is $123,650.00-$203,150.00. McAfee takes into consideration an individual's skillset, experience and location in making final salary determinations. For further details, please discuss with the Talent Acquisition Partner.
Please click here to view and download the Job Applicant Privacy Notice, which applies to all McAfee job applicants who are residents of the state of California.

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