Machine Learning Manager
About The Company:
At PathAI, we're applying computer vision, machine learning and AI in amazing ways to pathology data, impacting healthcare by improving detection and treatment selection for cancer as well as other diseases. This is accomplished by parallel efforts in drug development, the clinical space, and global health.
About The Team:
The Machine Learning team at PathAI is rapidly growing, with members tackling a wide range of computational pathology problems. These include cutting edge applications of machine learning to clinical prediction tasks, development and application of deep learning-based medical image processing systems, and ongoing medical device development work.
Tackling these challenging problems requires well-designed & well-implemented machine learning pipelines. We have built a comprehensive machine learning platform, specialized for computation pathology. It provides us user-friendly tooling for automating model exploration, training, and deployment. In parallel, we are continuously improving our machine learning platform and infrastructure, to increase efficiency, robustness, flexibility and automation.
What You’ll Do:
In this position, you will be part machine learning architect/engineer and part mentor/people manager. You’ll help improve our platform and projects so we can work more efficiently to improve patient lives.
- Hands-on Leadership: Work with and lead machine learning engineers and scientists. Expect this to be approximately 50% hands-on ML work and 50% people and team leadership.
- Technical Contribution: Work with ML team members in building tools that allow the whole team to tackle all our challenging and important problems in a more productive and automated way.
- Team Initiative Prioritization and Management: Support, plan and strategize for a wide variety of use cases, from experimental & research-oriented tasks to mission-critical & partner-specified tasks.
- 4+ years of industry experience having lead teams of 8-10+ ML Engineers and Scientists.
- Strong ability to efficiently model complex problems and architect and implement machine learning algorithms and associated tooling.
- Experience in AI, Machine Learning, NLP or Deep Learning. Familiar with Python, Tensorflow, scikit-learn, OpenCV.
- Advanced degree (Masters or PhD) in a quantitative field (computer science, machine learning, engineering, neuroscience, math, statistics, etc.)
- Insatiable intellectual curiosity and the ability to learn quickly in a sophisticated space.
For the right candidate, we'll offer a competitive salary plus equity. Your compensation is rounded out by a strong benefits package:
- Flexible work hours, with work-from-home options available for many roles
- Three weeks of paid leave per year, an additional two weeks of sick time, plus extended holidays and team-approved leave
- Ten days of 100% subsidized childcare per year
- Healthcare, vision, and dental insurance plans (HMO or PPO), with voluntary add-ons available for dependent care, life, and accident coverage
- Commuter benefit available for public transit or parking
- Convertible sit-stand desks
- Weekly in-office yoga classes
- Free in-office lunch on Tuesdays and Fridays
- Snacks and drinks in the office – which currently include a mountain of Milano cookies, endless Fruit Snacks, as well as cold brew coffee and kombucha on tap, among many other options. Our in-house Snackologist is also happy to take your requests!
Most importantly, you'll be doing important work with a team of people you'll genuinely enjoy spending the day with.
PathAI is an equal opportunity employer, dedicated to creating a workplace that is free of harassment and discrimination. We base our employment decisions on business needs, job requirements, and qualifications — that's all. We do not discriminate based on race, gender, religion, health, personal beliefs, age, family or parental status, or any other status. We don't tolerate any kind of discrimination or bias, and we are looking for teammates who feel the same way.
PathAI does not accept unsolicited submissions from third-parties.