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Aidoc

AI Software Tech Lead, ML

Tel Aviv-Yafo, Tel Aviv District, Israel

Location
Tel Aviv-Yafo, Tel Aviv District, Israel
Work
Hybrid
Employment
Not stated
Level
Lead / staff
Function
Data & AI
Pay
Not stated
Posted
2 months ago

About the role

About Aidoc

Aidoc is the market leader in healthcare AI and has developed the world's largest clinical frontier model, supporting nearly 50 million patients each year.

Aidoc is deployed in more than 2,000 medical centers worldwide. Since our founding in 2016, Aidoc has raised over $500 million and achieved a record number of FDA-cleared solutions.

Medical diagnosis is hitting a breaking point, where the number of physicians hasn't kept up with the rapidly growing patient load. This leads to misdiagnosis and treatment delays that result in hundreds of thousands of deaths every year. Aidoc assists clinicians by precisely highlighting diseases directly on medical images, preventing misdiagnosis and ensuring that urgent patients receive the immediate attention they need.

About this role

This is a AI Software Tech Lead, ML role within Aidoc’s AI Engineering group, focused on building and scaling the infrastructure behind advanced AI solutions in computer vision and NLP for medical imaging. The role combines hands-on software development, technical leadership, and close collaboration with cross-functional teams to transform AI innovation into scalable, high-impact products.

Responsibilities

  • Design, develop and lead SW development of infrastructure for innovative AI algorithms for computer vision and NLP in the context of medical imaging.
  • Collaborate with cross-functional teams, including researchers and product managers, to drive the development of new AI products and features.
  • Work in a unique professional culture applying the full range of software engineering capabilities in the core parts of the A.I. systems
  • Develop and maintain high-quality, scalable, and efficient code.
  • Take initiative in exploring and adopting of new technological advances in all relevant domains (for example, scalable cloud based systems, DL and CV SW frameworks, Large scale ML systems)

Requirements

  • BA/BSc/MSc in Computer Science, Engineering or a related field.
  • 7+ years of experience in developing large scale production systems – including architecture design, research, development and testing.
  • Deep understanding of Computer Science fundamentals – object-oriented design, code optimization, and complexity
  • Passion for building generic and robust software architecture
  • Passion for elegant and effective technological solutions, and a love for clean code
  • Strong experience with Python and advantage to deep learning frameworks such as TensorFlow, PyTorch, etc.
  • Strong ability to lead end-to-end development processes
  • Advantage: Experience in developing AI and machine learning solutions, with a focus on computer vision and NLP.
  • Strong communication and collaboration skills, with the ability to work effectively with a cross-functional team

Working at Aidoc

Our Perks

  • Be part of something big - using cutting-edge technologies to transform the Healthcare industry (while saving patients’ lives)
  • We work in a hybrid model, with our new offices located at 34 HaMasger Street in Tel Aviv and parking for employees.
  • Amazing and healthy breakfasts and lunches prepared daily by our personal chef!
  • Stocked up kitchen & meal card
  • Wellness: Aidoc employees-only gym, plus Pilates, Yoga, and functional workouts classes.
  • Amazing culture - collaborative, transparent & fun!
  • Attractive compensation package & benefits

Aidoc is deeply committed to creating an inclusive workplace, and to the principle of equal opportunity for all individuals. We prohibit discrimination and harassment based on race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, veteran status, or any other status protected by law.

Source

Posted by Aidoc on their own hiring page, job-boards.eu.greenhouse.io. OptiTalent shows it as published, read 07 Nov 2026 02:03 UTC; the original is the reference.

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