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Internship Applied Scientist Machine Learning Jobs

Adobe, Inc.

Applied Scientist 3

San Jose, CA · On-site

Join Adobe Firefly's Applied Science & Machine Learning (ASML) group and help advance content generation technologies powered by artificial intelligence. This role involves working closely with a ...

Adobe

Applied Scientist 3

San Jose, CA · On-site

Join Adobe Firefly's Applied Science & Machine Learning (ASML) group and help advance content generation technologies powered by artificial intelligence. This role involves working closely with a ...

Microsoft

Applied Scientist

Redmond, WA · On-site

$133.80K - $219.20K/yr

... GenAI and ML (Machine Learning) solutions that drive specific, measurable, and impactful ... relevant internship experience (e.g., statistics, predictive analytics, research) OR Master ...

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 ...

Apple

Applied ML Science Manager

Cupertino, CA · On-site

We are currently seeking an experienced and passionate Applied ML Science Manager to lead a dynamic ... Scientist, Machine Learning, or Data Scientist roleFamiliarity with a brand range of quasi ...

Microsoft AI

Senior Applied Scientist

Redmond, WA · On-site

In this role, you will design and implement machine learning models that power relevance systems ... other applied scientists to promote innovation. • Collaborate deeply across disciplines ...

Apple

Applied ML Science Manager

Cupertino, CA · On-site

$198.30K - $342.80K/yr

Description As an Applied ML Science Manager, you will have the responsibility of leading a highly ... Scientist, Machine Learning, or Data Scientist role Familiarity with a brand range of quasi ...

AEG

Data Scientist, Machine Learning

Orlando, FL · On-site

The Data Scientist, Machine Learning will support Basketball Operations by developing and deploying ... applied machine learning techniques, with fluency across tree-based methods, deep learning, and ...

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Internship Applied Scientist Machine Learning information

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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.

Scientist, Machine Learning

Atomic AI

South San Francisco, CA

$170K - $220K/yr

Other

Posted 29 days ago

Job description

At Atomic AI, we build artificial intelligence to pioneer new frontiers in drug discovery. Our unique R&D platform, an early version of which was featured on the cover of Science, provides new strategies to treat previously undruggable diseases by targeting RNA. We continue to advance this platform by developing new machine learning methods and unique foundation models fueled by our large-scale, in-house experimental data collection. We are an interdisciplinary team of scientists and engineers and believe our people are our greatest strength and the key to our success.

The opportunity

As a full-time Scientist on the Machine Learning team, you will work closely with engineers and experimental scientists to advance our technology platform for RNA structure prediction, target identification, and early drug discovery. You will co-lead the development and evaluation of the machine learning pipeline. You will contribute new ideas and realize their potential as part of a continuously advancing state-of-the-art platform. You will proactively shape the directions of the machine learning efforts and those of the whole company. 

Primary responsibilities

  • Design and develop novel machine learning models for RNA structure prediction and drug targeting.
  • Evaluate and advance the state of the art of our structure prediction platform.
  • Collaborate with our wetlab team on the targeted acquisition of experimental data to improve our machine learning models.
  • Develop high-quality code in a team setting.
  • Analyze, interpret, and organize results and present progress to colleagues in regular research meetings.
  • Work within a collaborative, high-caliber, interdisciplinary team and proactively shape the scientific and strategic vision of the company.

About you

  • Ph.D., M.Sc., or M.Eng. in Computer Science, Physics, Applied Mathematics, Materials Science, Computational Biology, or related field.
  • 4+ years of experience developing machine learning methods for scientific applications.
  • Foundational knowledge of machine learning and underlying mathematical concepts.
  • Proficiency in Python and deep learning frameworks (e.g., JAX, PyTorch).
  • Excellent presentation and writing skills, able to clearly communicate technical information to colleagues.

Pluses

  • Publications at major machine learning conferences or in major scientific journal
  • Research experience related to structural biology, molecular design, and drug discovery.
  • Foundational knowledge of physics, chemistry, and molecular biology.
  • Demonstrated ability to develop performant code.

Salary Range (all levels): $170,000/year to $220,000/year + equity + benefits. This range reflects variations in seniority, expertise, and skills.

About Atomic AI

Sourced by ZipRecruiter

Industry

Biotechnology research and development

Company size

11 - 50 Employees

Headquarters location

South San Francisco, CA, US

Year founded

2021

Social media

Twitter

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