AI/Data Science Team Manager (Medtech)
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
TL;DR
AI/Data Science Team Manager (ML/Computer Vision): Leading a team of researchers to develop AI-driven algorithmic solutions for lung cancer diagnosis medical devices with an accent on machine learning, computer vision, and image processing. Focus on driving the end-to-end algorithm development lifecycle from research and prototyping to production-ready medical technology.
Location: Herzliya, Tel Aviv, Israel
Company
A global leader in healthcare technology dedicated to alleviating pain, restoring health, and extending life through innovative medical devices.
What you will do
- Lead a high-performing team of researchers to develop ML, Computer Vision, and Image Processing solutions for surgical robotics.
- Manage the full algorithm development lifecycle including research, design, implementation, validation, and optimization.
- Collaborate with Data, Software, Systems, Clinical, and Product teams to define requirements and manage end-to-end delivery.
- Represent the algorithm team in global forums and communicate progress and risks to stakeholders.
- Provide technical direction and mentorship to developers through design and code reviews.
Requirements
- B.Sc. in Computer Science, Software Engineering, EE, or a related field.
- 7+ years of R&D experience in algorithms and Machine Learning.
- Proven leadership experience as a team lead or tech lead, including mentoring and prioritization.
- 3+ years of hands-on experience with production-quality Python code.
- Proven experience deploying deep learning and AI models into production environments.
- Must be based in Herzliya or Tel Aviv, Israel
Nice to have
- MSc or PhD in Computer Science, Software Engineering, or EE.
Culture & Benefits
- Competitive salary and flexible benefits package.
- Eligibility for the Incentive Plan (MIP).
- Innovation-driven environment that encourages curiosity and bold thinking.
- Opportunity to develop technology with direct clinical impact on patients' lives.
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