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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 ...

Ramp

Senior Applied Scientist, Credit Risk

New York, NY · On-site

$165K - $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 - $140K/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 ...

Fuze Health

OR

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 ...

Grid

Applied Scientist

Seattle, WA

$120K - $140K/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

$175K - $308K/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 ...

Apple

Applied Scientist

Austin, TX

$175K - $308K/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 ...

Adobe, Inc.

Senior Applied Scientist

San Jose, CA · On-site

$107K - $146K/yr

Adobe Firefly's Applied Science & Machine Learning (ASML) group invites an Applied Scientist / Machine Learning Engineer passionate about post-training and distillation of large generative AI models ...

Grid

Staff Applied Scientist

Seattle, WA · On-site

$150K - $220K/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 ...

Adobe

Senior Applied Scientist

San Jose, CA

$107K - $146K/yr

Adobe Firefly's Applied Science & Machine Learning (ASML) group invites an Applied Scientist / Machine Learning Engineer passionate about post-training and distillation of large generative AI models ...

Grid

Staff Applied Scientist

Seattle, WA · On-site

$150K - $220K/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 ...

Adobe

Senior Applied Scientist

Seattle, WA

$104K - $142K/yr

Adobe Firefly's Applied Science & Machine Learning (ASML) group invites an Applied Scientist / Machine Learning Engineer passionate about post-training and distillation of large generative AI models ...

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Internship Applied Scientist Machine Learning information

See salary details

$25.5K

$42.6K

$88K

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

As of Aug 6, 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 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.
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:
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Internship Applied Scientist Machine Learning jobs near you
Infographic showing various Internship Applied Scientist Machine Learning job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 72% Full Time, 24% Part Time, 1% Temporary, and 2% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $42,584 per year, or $20.5 per hour.

Staff Applied Scientist - Machine Learning

Rokt

Austin, TX • Hybrid

$470K - $615K/yr

Full-time

Medical, Dental, Vision, Retirement, PTO

Posted 14 days ago

Job description

Rokt is an ecommerce technology company with the mission of making every transaction more relevant. The Rokt ecommerce Network leverages proprietary machine learning systems, powering billions of transactions for hundreds of millions of customers, and is trusted to do this by companies like Live Nation, Fanatics, Macy's, AMC Theatres, PayPal, Uber, Hulu, Staples, Albertsons and HelloFresh.
The Role: As a Staff Applied Scientist in the Rokt Brain team, you will lead applied research, experimentation, and model development projects - harnessing a diversity of ML theories, concepts, and models to improve complex systems powering 10 billion+ transactions per year.
Growth: pathways to Principal Applied Scientist (IC Track) and Applied Science Manager/Director (People Leader track) per your preferences and abilities.
Pay: Target total compensation ranges from $470k - $615k, comprised of a fixed annual salary of $290k - $360k, plus employee equity plan grant. In addition, you will receive world-class employee benefits.

Responsibilities:
Technical

  • Own the research, design, development, testing, deployment and maintenance of machine learning systems and services at Rokt. 
  • Optimise auction and decisioning logic, applying model predictions to maximise value across Rokt's multi-sided marketplace
  • Conduct applied ML research, prototype new modeling approaches, and rigorously test innovations.
  • Evaluate and improve model performance, ensuring robustness, scalability, and interpretability.
  • Translate complex business needs into practical ML solutions, collaborating with product and engineering teams.
  • Stay ahead of emerging ML trends, contributing to knowledge sharing through tech talks, brown bags, and best practice evangelism.

Leadership

  • Act as technical and project leader of a small team of specialists
  • Provide leadership on complex technical issues, 
  • Set standards for technical excellence - from coding to architectural best practices.
  • Work cross-functionally with engineering and product leadership to plan and manage delivery expectations of roadmap items.
  • Actively monitor progress and intervene where required to mitigate risks and bottlenecks, managing expectations within and outside the team.

Requirements

  • PhD or equivalent experience in Computer Science, Statistics, Mathematics, or related field with specialization in ML, AI, or Information Retrieval, and experience leading PhD level scientists/engineers on projects.
  • 10+ years of industry experience building production-grade ML systems.

+ Deep expertise in at least two of the following:

  • ML for Ads, E-commerce, or Two-Sided Marketplaces
  • Deep Learning Architectures e.g MMoE, PLE, DCN, Transformers, Graph Neural Networks
  • Bayesian Modelling & Probabilistic Methods
  • Reinforcement Learning (Contextual Bandits, Policy Optimization)
  • Price & Revenue Optimisation
  • Representation Learning & Embeddings
  • Model Optimisation (quantisation, distributed training, GPU optimisation, JIT compilation, mixed precision, inference optimisation)
  • Knowledge Distillation

Hybrid work structure:
Rokt has a 4 day in-office, 1 day remote hybrid structure - with a flexible approach to start/finish times.

Benefits

  • Equity in a profitable, fast-growing company approaching $1 Billion in revenue.
  • Dollar-for-dollar 401K matching plan (up to 4% of fixed annual remuneration)
  • Fully funded health insurance (Dental, Optical, and Medical)
  • Generous allowances for wellness, technology, mobile, and transit.
  • Daily catered lunch, stocked pantry & fridges
  • Extra leave (bonus annual leave, sabbatical leave etc.)

Equal employment opportunities are available to all applicants without regard to race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.

If this sounds like a role you'd enjoy, apply here, and you'll hear from our recruiting team.

Note: The first stage of Rokt's recruitment process is a 15-minute online aptitude test, which will be sent out to your application email. Successful candidates will be contacted on next steps.

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