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Biology Machine Learning Intern Jobs in Seattle, WA

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Biology Machine Learning Intern information

See Seattle, WA salary details

$29K

$48.5K

$100.1K

How much do biology machine learning intern jobs pay per year?

As of Sep 1, 2026, the average yearly pay for biology machine learning intern in Seattle, WA is $48,461.00, according to ZipRecruiter salary data. Most workers in this role earn between $37,000.00 and $52,300.00 per year, depending on experience, location, and employer.

What does a biology machine learning intern do?

A Biology Machine Learning Intern works at the intersection of biology and computer science, applying machine learning techniques to analyze biological data. Their tasks often include processing large datasets, building predictive models, and supporting research projects that use artificial intelligence to solve biological problems. Interns may work on projects like drug discovery, genomics, or protein structure prediction, and typically collaborate with scientists and engineers. This role helps bridge the gap between experimental biology and data-driven insights.

What kinds of projects does a biology machine learning intern typically work on, and how do these projects contribute to the team?

Biology Machine Learning Interns often work on interdisciplinary projects that apply machine learning techniques to analyze biological data, such as genomics, protein structures, or cellular imaging. These projects may involve developing predictive models, automating data processing pipelines, or extracting meaningful patterns from large, complex datasets. Interns usually collaborate closely with both biologists and data scientists, gaining hands-on experience and contributing valuable insights that support ongoing research or product development. This collaborative environment not only enhances technical skills but also provides exposure to real-world applications of AI in life sciences.

What are the key skills and qualifications needed to thrive as a biology machine learning intern, and why are they important?

To thrive as a Biology Machine Learning Intern, you need a foundational understanding of biology, statistics, and programming (usually Python or R), often supported by coursework or a degree in a related field. Familiarity with machine learning frameworks (such as TensorFlow or scikit-learn), bioinformatics tools, and data analysis platforms is typically expected. Strong problem-solving abilities, attention to detail, and teamwork skills help interns excel in interdisciplinary research environments. These skills and qualities are crucial for effectively analyzing biological data, developing models, and contributing to innovative scientific solutions.

What job categories do people searching Biology Machine Learning Intern jobs in Seattle, WA look for?

The top searched job categories for Biology Machine Learning Intern jobs in Seattle, WA are:

Infographic showing various Biology Machine Learning Intern job openings in Seattle, WA as of August 2026, with employment types broken down into 1% As Needed, 75% Full Time, 22% Part Time, and 2% Contract. Highlights an 88% Physical, 2% Hybrid, and 10% Remote job distribution, with an average salary of $48,461 per year, or $23.3 per hour.

AI Scientist Intern, Computational Protein Design

Xaira Therapeutics

Seattle, WA โ€ข On-site

$10K - $15K/mo

Internship

Posted 3 days ago

New


Job description

About the Role

As an AI Scientist Intern on our Computational Protein Design team, you will work alongside talented scientists and engineers developing generative AI models for protein and antibody therapeutic design. During your internship, you will contribute to advancing state-of-the-art machine learning models for biology, with a focus on impacting protein/antibody design and drug discovery. You will also have the opportunity to collaborate with interdisciplinary experts in biology, drug discovery, and clinical research.

Responsibilities

  • Develop and apply deep learning methods for protein/antibody structure, sequence, or property modeling, under the guidance and mentorship of experienced scientists and engineers
  • Implement and train models on GPUs using PyTorch
  • Contribute to ongoing research projects involving protein structure, sequence, or biophysical/affinity datasets
  • Participate in discussions to help generate innovative ideas for advancing AI methodologies in computational protein design
  • Document findings and communicate progress effectively to peers and mentors

Qualifications

  • Currently pursuing a MS or PhD in Computer Science, Machine Learning, or a related technical field, with strong publication record
  • Hands-on experience with PyTorch and training/inference of AI models on GPUs
  • Strong interest in AI innovation and its applications to interdisciplinary fields such as biology and chemistry
  • Extensive hands-on experience with deep learning methods and frameworks
  • Ability to work collaboratively in a team environment and learn from experienced mentors
  • A scientifically curious mindset with a passion for exploring new challenges
  • Experience with large-scale distributed training and inference is a plus
  • Exposure to molecular structure or biological sequence data or computational biology/bioinformatics is a plus, but not required
  • Prior research experience demonstrated through publications and/or significant open source code authorship
  • Interest in contributing to open-source deep learning libraries and frameworks is a plus

Internship Duration
3 months
The expected monthly compensation range is $10,000-$15,000, depending on experience and qualifications. We are open to higher compensation for candidates with exceptional experience or impact. This internship is designed to provide a unique learning experience, offering hands-on exposure to the intersection of AI and computational protein design while allowing you to contribute meaningfully to real-world projects.