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Weekday Machine Learning Research Scientist Jobs in Minnesota

Kitware

Machine Learning Engineer

Minneapolis, MN · On-site

$85K - $125K/yr

Machine learning experience using visual data * Understanding of a variety of machine learning ... Kitware is a research and development software solutions provider with a mission to advance science ...

Kitware

Machine Learning Engineer

Minneapolis, MN · On-site

$85K - $125K/yr

Machine learning experience using visual data * Understanding of a variety of machine learning ... Kitware is a research and development software solutions provider with a mission to advance science ...

Kitware

Machine Learning Engineer

Minneapolis, MN · On-site

$85K - $125K/yr

Machine learning experience using visual data * Understanding of a variety of machine learning ... Kitware is a research and development software solutions provider with a mission to advance science ...

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All JobsWeekday Machine Learning Research Scientist JobsWeekday Machine Learning Research Scientist Jobs in Minnesota

Weekday Machine Learning Research Scientist information

What are the key skills and qualifications needed to thrive as a Weekday Machine Learning Research Scientist, and why are they important?

To thrive as a Weekday Machine Learning Research Scientist, you need a solid background in mathematics, statistics, programming (Python, R), and a relevant advanced degree such as a Master's or Ph.D. in computer science or a related field. Expertise with machine learning frameworks (like TensorFlow, PyTorch), data processing tools, and familiarity with cloud computing platforms are typically required. Strong analytical thinking, problem-solving abilities, and clear communication skills help you collaborate with teams and present complex findings effectively. These skills are crucial for developing innovative models, delivering impactful research, and ensuring successful implementation in real-world applications.

What does a Weekday Machine Learning Research Scientist do?

A Weekday Machine Learning Research Scientist conducts research and develops new algorithms or models in the field of machine learning, typically during standard business days (Monday to Friday). Their work involves designing experiments, analyzing data, publishing findings, and collaborating with other scientists or engineers. They may focus on improving existing machine learning techniques or creating innovative solutions for real-world problems. This role often requires a strong background in mathematics, computer science, and statistics, as well as proficiency in programming languages like Python or R.

What are some common challenges faced by a Weekday Machine Learning Research Scientist, and how are they typically addressed within the team?

Weekday Machine Learning Research Scientists often encounter challenges such as managing large datasets, tuning complex models, and keeping up with rapidly evolving research. Collaboration is key—team members regularly hold meetings to share findings, brainstorm solutions, and review code. Access to robust computational resources and mentorship from senior researchers helps address technical obstacles, while a structured, weekday schedule allows for focused research and effective work-life balance.

What is the difference between Weekday Machine Learning Research Scientist vs Weekend Machine Learning Research Scientist?

AspectWeekday Machine Learning Research ScientistWeekend Machine Learning Research Scientist
CredentialsMaster's or PhD in Computer Science, Data Science, or related fieldsSame as weekday role
Work EnvironmentTypically in office or research labs during standard hoursFlexible hours, often part-time or project-based
Employer & Industry UsageTech companies, research institutions, startupsFreelance projects, consulting firms, academic collaborations

The main difference between a Weekday Machine Learning Research Scientist and a Weekend Machine Learning Research Scientist lies in their work schedule and environment. Weekday roles usually involve full-time employment with structured hours, while weekend roles are often part-time or freelance, offering more flexibility. Both roles require similar credentials and are used across tech and research industries.

Weekday Machine Learning Research Scientist jobs near you
Research Scientist Intern (2025)

Research Scientist Intern (2025)

Whiterabbit.ai

Plymouth, MN • On-site

Other

Re-posted 24 days ago

Job description

We are looking for a Research Scientist Intern to push the state of the art of our AI models. As a Research Scientist Intern at Whiterabbit.ai, you will:

  • Play a key role in architecting the algorithms and models that will power our products
  • Train on a dedicated high-performance compute cluster specialized for deep learning research
  • Work with doctors and healthcare professionals to identify serious problems and leverage their domain expertise to build robust solutions
  • Remain an active contributor to the research community by partnering with universities and publishing high impact papers

Who we are:

Our mission at Whiterabbit.ai is to save lives and eliminate suffering through the early detection of cancer with artificial intelligence. We collaborate closely with one of the top medical schools in the country and have exclusive access to one of the world’s largest cancer datasets with millions of images. We invent algorithms that make doctors more productive, more accurate, and more capable. We build products and services with a relentless focus on transforming the patient’s healthcare experience.

Responsibilities

  • Develop highly scalable classifiers and detectors that solve real-world problems
  • Learn and understand a large body of research in deep learning and machine learning
  • Participate in cutting-edge research for medical applications of computer vision

Must Have Experience

  • Experience with deep learning and convolutional networks
  • Strong theoretical and empirical research background
  • Fluency with a deep learning framework and Python

Nice to Have Experience

  • Contributions to research communities and efforts, such as publications at conferences like CVPR, NeurIPS, ICCV, ECCV, ICML, and ICLR
  • Large scale machine learning experience working with terabytes of data
  • Implemented custom operations/modules in a deep learning framework
  • Imagination, ambition, and curiosity

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