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Bioinformatics Machine Learning Internship Jobs in Madison, WI

Experience managing bioinformatics pipelines in Unix/Linux environments. * Data Analysis & Machine Learning: Strong skills in data mining, machine learning (deep learning, pattern recognition), and ...

Experience managing bioinformatics pipelines in Unix/Linux environments. * Data Analysis & Machine Learning: Strong skills in data mining, machine learning (deep learning, pattern recognition), and ...

Experience managing bioinformatics pipelines in Unix/Linux environments. * Data Analysis & Machine Learning: Strong skills in data mining, machine learning (deep learning, pattern recognition), and ...

Experience managing bioinformatics pipelines in Unix/Linux environments. * Data Analysis & Machine Learning: Strong skills in data mining, machine learning (deep learning, pattern recognition), and ...

Experience managing bioinformatics pipelines in Unix/Linux environments. * Data Analysis & Machine Learning: Strong skills in data mining, machine learning (deep learning, pattern recognition), and ...

Experience managing bioinformatics pipelines in Unix/Linux environments. * Data Analysis & Machine Learning: Strong skills in data mining, machine learning (deep learning, pattern recognition), and ...

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Bioinformatics Machine Learning Internship information

See Madison, WI salary details

$25.7K

$42.9K

$88.7K

How much do bioinformatics machine learning internship jobs pay per year?

As of May 28, 2026, the average yearly pay for bioinformatics machine learning internship in Madison, WI is $42,908.00, according to ZipRecruiter salary data. Most workers in this role earn between $32,700.00 and $46,400.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Bioinformatics Machine Learning Intern, and why are they important?

To thrive as a Bioinformatics Machine Learning Intern, you need a solid background in biology, statistics, and computer science, typically supported by relevant coursework or a degree in bioinformatics, computational biology, or a related field. Familiarity with programming languages like Python or R, experience using bioinformatics tools (e.g., BLAST, Bioconductor), and knowledge of machine learning frameworks such as TensorFlow or scikit-learn are highly valued. Attention to detail, problem-solving skills, and effective communication help interns collaborate on interdisciplinary teams and interpret complex datasets. These skills ensure interns can contribute meaningfully to research projects, derive insights from biological data, and communicate findings clearly.

What are some typical projects or tasks a Bioinformatics Machine Learning Intern might work on during their internship?

As a Bioinformatics Machine Learning Intern, you'll often contribute to projects that involve developing and testing algorithms for analyzing biological data, such as genomic sequences or protein structures. Typical tasks may include preprocessing large datasets, implementing machine learning models to identify patterns or make predictions, and visualizing results for team discussions. Interns frequently collaborate with both computational scientists and experimental biologists, gaining exposure to interdisciplinary teamwork and real-world applications. This hands-on experience helps interns build both technical and domain-specific skills, preparing them for advanced roles in bioinformatics or data science.

What is a Bioinformatics Machine Learning Internship?

A Bioinformatics Machine Learning Internship is a temporary position, usually for students or recent graduates, where interns gain hands-on experience applying machine learning techniques to biological data. Interns may work on projects like analyzing genomic sequences, predicting protein structure, or developing algorithms for biomedical research. The role involves coding, data analysis, and collaborating with scientists to solve real-world biological problems. It offers exposure to both computational methods and biological sciences, preparing interns for careers in bioinformatics, data science, or research.

What is the difference between Bioinformatics Machine Learning Internship vs Bioinformatics Data Analyst Internship?

AspectBioinformatics Machine Learning InternshipBioinformatics Data Analyst Internship
Required SkillsProgramming, machine learning, bioinformatics toolsData analysis, statistical skills, bioinformatics tools
Work EnvironmentResearch labs, biotech companies, academic institutionsResearch labs, healthcare, biotech firms
Industry UsageDeveloping algorithms, predictive models in bioinformaticsAnalyzing biological data, generating reports

While both internships involve bioinformatics, the Bioinformatics Machine Learning Internship focuses on developing machine learning models and algorithms, whereas the Bioinformatics Data Analyst Internship emphasizes analyzing biological data and generating insights. Both roles require programming and bioinformatics skills but differ in their core focus and application.

What are the most commonly searched types of Bioinformatics Machine Learning jobs in Madison, WI? The most popular types of Bioinformatics Machine Learning jobs in Madison, WI are:
What job categories do people searching Bioinformatics Machine Learning Internship jobs in Madison, WI look for? The top searched job categories for Bioinformatics Machine Learning Internship jobs in Madison, WI are:
Sr. Engineer, Machine Learning Operations

Sr. Engineer, Machine Learning Operations

Exact Sciences

Madison, WI

$209K/yr

Full-time, Part-time

Medical, Dental, Vision, Retirement, PTO

Posted 26 days ago


Exact Sciences rating

8.5

Company rating: 8.5 out of 10

Based on 54 frontline employees who took The Breakroom Quiz

19th of 103 rated laboratories


Job description

Help us change lives

At Exact Sciences, we’re helping change how the world prevents, detects and guides treatment for cancer. We give patients and clinicians the clarity needed to make confident decisions when they matter most. Join our team to find a purpose-driven career, an inclusive culture, and robust benefits to support your life while you’re working to help others.

Position Overview

The Sr. Engineer, Machine Learning Operations, with minimal guidance, works independently and with cross‑functional partners—including biostatisticians, bioinformatics scientists, AI scientists, and software engineers—to deploy, operate, and scale machine learning solutions in production for advanced cancer screening and precision oncology applications. The role designs, builds, and maintains robust ML platforms and pipelines that ensure reliability, security, and compliance across the full model lifecycle—from data ingestion, model training, versioning and evaluation, through deployment, monitoring, and continuous improvement. This role serves as a key resource, applying in‑depth practical knowledge of ML Operations, software engineering, and cloud infrastructure to solve complex problems across multiple projects, ensuring AI/ML models are production-ready, observable, and aligned with the company's mission to help eradicate cancer.

Essential Duties

Include, but are not limited to, the following:

  • Designs, implements, and maintains end‑to‑end MLOps pipelines for training, validation, deployment, and monitoring of ML and AI models used in cancer screening and precision oncology solutions.
  • Builds and operates scalable, secure ML infrastructure on cloud and container platforms (e.g., AWS/Azure/GCP, Docker, Kubernetes) to support batch and real‑time inference workloads.
  • Implements CI/CD workflows for ML (data, model, and code), including automated testing, packaging, and promotion of models across development, staging, and production environments.
  • Establishes and manages model and data versioning, experiment tracking, and lineage to ensure reproducibility, auditability, and effective model governance.
  • Develops and maintains monitoring, logging, and alerting for model performance, data quality, drift, and system health, defining and meeting SLOs/SLAs for critical ML services.
  • Collaborates with data scientists, bioinformatics and biostatistics partners, and software/platform engineering teams to translate experimental workflows into production‑grade services integrated into customer‑facing and internal applications.
  • Uphold company mission and values through accountability, innovation, integrity, quality, and teamwork.
  • Support and comply with the company’s Quality Management System policies and procedures.
  • Maintain regular and reliable attendance.
  • Ability to act with an inclusion mindset and model these behaviors for the organization.
  • Ability to work on a mobile device, tablet, or in front of a computer screen and/or perform typing for approximately 90% of a typical working day.
  • Ability to travel 5% of working time away from work location, may include overnight/weekend travel.

Minimum Qualifications

  • Bachelor’s Degree in a field related to essential duties; or Associates Degree and 2 years of relevant experience.; or High School Diploma or General Education Degree (GED) and 4 years of relevant experience.
  • 5 years of relevant job-related experience.
  • Demonstrated experience with Python, at least one major ML framework (e.g., TensorFlow, PyTorch, scikit‑learn), containerization and orchestration technologies (e.g., Docker, Kubernetes), and a major cloud platform (e.g., AWS, Azure, GCP) supporting ML workloads.
  • Demonstrated ability to perform the essential duties of the position with or without accommodation.
  • Applicants must be currently authorized to work in country where work will be performed on a full or part-time basis. We are unable to sponsor or take over sponsorship of employment visas at this time. 

Preferred Qualifications

  • 2+ years of life sciences industry experience working with biological data.
  • 2+ years of industry experience in molecular diagnostics, preferably cancer diagnostics.
  • Expertise in data mining approaches within healthcare settings generating insight from routinely collected healthcare data.
  • Scientific understanding of cancer biology
  • Strong programming ability in Python and experience with at least one major ML framework (e.g., TensorFlow, PyTorch, scikit-learn).
  • Hands-on experience deploying and operating machine learning models in production, including experience with CI/CD pipelines, model packaging, and automated deployment.
#LI-CB1

Salary Range:

National Ranges: $ 123,000.00 - $209,000.00

California Ranges: $152,000.00- $228,000.00

 

The annual base salary shown is a national range for this position on a full-time basis and may differ by hiring location. In addition, this position is bonus eligible.

 

Exact Sciences is proud to offer an employee experience that includes paid time off (including days for vacation, holidays, volunteering, and personal time), paid leave for parents and caregivers, a retirement savings plan, wellness support, and health benefits including medical, prescription drug, dental, and vision coverage. Learn more about our benefits.

Our success relies on the experiences and perspectives of a diverse team, and Exact Sciences fosters a culture where all employees can develop personally and professionally with a sense of respect and belonging. If you require an accommodation, please contact us here.

Not ready to apply? Join our Talent Community to stay updated on the latest news and opportunities at Exact Sciences.

We are an equal employment opportunity employer. All qualified applicants will receive consideration for employment without regard to disability, protected veteran status, and any other status protected by applicable local, state, or federal law.

To view the Right to Work, E-Verify Employer, and Pay Transparency notices and Federal, Federal Contractor, and State employment law posters, visit our compliance hub. The documents summarize important details of the law and provide key points that you have a right to know.


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