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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 my day with?

• You will work in the cancer screening group of 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 (5 nationalities!), experience, and interests.
• We have an open and free culture. Most people love to socialize and chat, but you are not expected to and are also free to opt-out.

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.

🗨️ About the position

What will make me proud to work here?

• You will be able to make a direct impact on our mission to conquer cancer through AI, by contributing to software that is used in real hospitals around the world.
• Your work will push forward our AI research frameworks, inference engines, and performance of the 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, 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.
• 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.
• Enhance the maintainability, reliability, and efficiency of both new and existing AI software for various applications in cancer screening.
• Produce high-quality software by refactoring existing research frameworks or adopting new technologies and libraries
• Create innovative medical AI models by implementing or proposing cutting-edge methodologies and contributing to research projects.
• 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
• General: Git, Docker, Confluence, Jira

Requirements

🎯 Qualifications

• 2+ years of professional experience in the IT industry
• Experience in machine learning engineering or research engineering in the AI industry
• 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
• Passion for machine learning engineering, research, and software engineering’s best practices

🏅 Preferred Experiences

• Experience with parallel, distributed, and cloud computing (e.g., GCP, AWS, or Azure)
• Experience with frameworks like TensorRT and openVINO
• Ability to communicate and write technical reports in English
• Contributions to open-source repositories in computer vision, machine
• Stimulate and push various initiatives within a team, e.g., code refactoring, dissemination of knowledge, culture-related events, etc
• 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)
• 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)