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(Global) Research Engineer

Remote: 
Full Remote
Contract: 
Experience: 
Mid-level (2-5 years)
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Offer summary

Qualifications:

4+ years IT experience in ML engineering/research engineering, Experience in Python, machine learning frameworks & MLOps, B.Sc., M.Sc, or Ph.D. in computer science or related field, Strong attention to detail and team player, Passion for machine learning, research & best practices.

Key responsabilities:

  • Develop high-quality medical AI frameworks and products
  • Contribute to large-scale inference engines for healthcare
  • Advocate for code quality and software architecture standards
  • Create innovative AI models with cutting-edge methodologies
  • Mentor team and collaborate on impactful projects
Lunit logo
Lunit https://www.lunit.io/
201 - 500 Employees
See more Lunit offers

Job description

"Conquering cancer through AI"

Lunit, a portmanteau of ‘Learning unit,’ is a medical AI software company devoted to providing AI-powered total cancer care.

Our AI solutions help discover cancer and predict cancer treatment outcomes, achieving timely and individually-tailored cancer treatment.

🗨️ About the team

Who will I spend day with?

  • You will work in the AI research department, with a group of enthusiastic and talented AI Researchers and Engineers. We contribute to real-world products, while also solving meaningful and applied research projects.
  • The teams and members of the department have diverse cultural backgrounds (9 nationalities!), experience, and interests.

How do they bond as a team?

  • Our team fosters a friendly and open environment, encouraging idea sharing and collaboration in research, engineering, and team events. Activities include research seminars, research workshops, attending top-tier conferences, and team meals.

🗨️ About the position

What will make me proud to work here?

  • You will have a direct impact on our mission to Conquer Cancer Through AI by contributing to more personalized treatment planning for cancer patients or early diagnosis of cancer. Our software has been recognized as best-in-class worldwide and is being used in real-world hospitals, laboratories, and research studies.
  • Your work will push forward our AI research frameworks, inference engines, and performance of Lunit’s AI models. Lunit has best-in-class products thanks to these components.
  • We have access to very large in-house labeled and unlabeled datasets. And, the cloud computing power to leverage them.
  • Current projects span a variety of topics, including but not restricted to object detection, semantic segmentation, large-scale self-supervised learning, domain generalization, active learning, multi-task learning, and ML pipelines, among others.
  • We contribute back to the community through publications, blog posts, dataset releases, and the organization of public events such as machine learning challenges or tutorials.
  • Experience personal and professional growth by working on diverse projects and collaborating with talented multi-disciplinary teams.

🚩 Roles & Responsibilities

  • Develop, and implement high-quality medical AI research frameworks, ML pipelines, and products for advancing healthcare.
  • Contribute to large-scale and distributed inference engines for medical AI applications.
  • Enhance the maintainability, reliability, and efficiency of both new and existing AI software for medical AI applications.
  • Advocate for and uphold high standards in code quality, and software architecture, including the refactoring of research frameworks or the adoption of new technologies and libraries.
  • Create innovative medical AI models by implementing or proposing cutting-edge methodologies and contributing to research projects.
  • Be the technical lead of impactful research engineering projects and design the next level of the ML pipelines with other stakeholders.
  • Mentor other research engineers, and contribute to attracting and retaining highly qualified engineers.
  • Collaborate closely with research scientists, engineers, and medical doctors on diverse real-world AI projects.

🚩 Tools Used

  • Programming languages/framework: Python, PyTorch, MLFlow, Ray, Prefect.
  • Infrastructure: Google Cloud Platform.
  • Tools: Git, Docker, Confluence, Jira.

Requirements

🎯 Qualifications

  • 4+ years of professional experience in the IT industry.
  • Experience in machine learning engineering or research engineering in the AI industry.
  • Solid experience with Python, unit/integration testing, documentation, Git, collaborative code development, MLOps, and Docker.
  • Familiarity with machine learning frameworks and platforms(e.g., PyTorch, Tensorflow, MLFlow).
  • Experience in bringing machine learning-based software to production.
  • B.Sc., M.Sc, or Ph.D. degree in computer science or a related field.
  • Keen eye and attention to detail.
  • Team player with experience working in teams with 3+ members.
  • Experience in leading machine learning engineering projects.
  • Passion for machine learning engineering, research, and software engineering’s best practices.
  • Ability to learn and evaluate new relevant technologies.

🏅 Preferred Experiences

  • Experience with parallel, distributed, and cloud computing (e.g., GCP, AWS, or Azure)
  • Ability to communicate and write technical reports in English.
  • Interest in mentoring other fellow engineers.
  • Stimulate and push various initiatives within a team, e.g., code refactoring, dissemination of knowledge, culture-related events, etc.
  • Experience with large (bio)medical imaging or histopathology data.
  • Contributions to open-source repositories in Computer Vision, Machine Learning, or related areas.
  • Participation in competitive Computer Vision/Medical Imaging challenges.
  • Strong desire to have an impact in healthcare and conquer cancer through AI.

📝How to Apply

  • CV (resume, free format, in English)

🏃‍♀️ Hiring Process

  • Document Screening → Introductory Interview → Assignment → Competency-based interview → Culture-fit Interview → Onboarding
    • Competency interview Includes two parts:
      • A short presentation describing the assignment
      • Technical Interview
    • All interviews are conducted in English
    • After the final interview, we may proceed with reference checks if needed

🤝 Work Conditions and Environment

  • Work type: Full-time
  • Work location : Lunit HQ(5F, 374, Gangnam-daero, Gangnam-gu, Seoul)
    • Alternatively: fully-remote in France, Germany, Netherlands, UK
  • Salary: After negotiation

🎸 ETC

  • If you misrepresent your experience or education or provide false or fraudulent information in or with your application, it may be grounds for cancellation of the employment.
  • Lunit is committed in providing the preferential processing to those eligible for employment protection (national merits and people with disabilities) relevant to related laws and regulations.

Benefits

🌻 Benefits & Perk

  • The new office is one minute away by foot from Gangnam Station Exit 3 making it very convenient
  • Up to 12, 000 won is covered for both lunch and dinner when working at the office.
  • Up to 300,000 won is covered upon joining to decorate your personal workspace
  • Provide the latest computer models, such as Macs and 4K monitors, and renew them every three years
  • Attending seminars and purchasing books are covered
  • Regular in-house AI and medical seminars are held
  • Korean language education is provided for Lunitians who do not speak Korean as their first language
  • Access high-quality AI learning resources & deep learning DevOps system
  • Up to 1.2 million won worth of benefits points can be claimed annually
  • Korean National holiday gift: Seollal and Chuseok gift/voucher
  • Annual medical checkups and employee accident insurance are provided
  • Financial support for participation in employee gatherings (once a month)

Required profile

Experience

Level of experience: Mid-level (2-5 years)
Spoken language(s):
KoreanEnglish
Check out the description to know which languages are mandatory.

Other Skills

  • Verbal Communication Skills
  • Leadership Development
  • Open Mindset
  • Detail Oriented

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