About this role
Who we are looking for
We’re looking for a Staff AI/ML Engineer to take technical ownership of our AI/ML work end-to-end. You’ll work on complex AI/ML problems, lead projects from idea to implementation, and help shape how we build and scale AI across the company. You’ll bring hands-on experience building and leading projects end-to-end, along with the ability to go deep into technical decisions, edge cases, and trade-offs.
Your mission
Solve complex problems using the right AI/ML approach, from classic ML to GenAI and LLMs, depending on the problem.
Design AI/ML systems and architecture, including greenfield projects.
Evaluate, monitor, and maintain AI/ML pipelines in production — not only build AI/ML solutions, but also assess their performance and keep them reliable over time.
Audit our current AI setup and help define the AI strategy and roadmap.
Lead cross-functional AI initiatives and drive them from idea to implementation.
Challenge existing technical decisions constructively and stay focused on the product and the result.
Your background
Proven experience leading AI/ML projects end-to-end in a startup/product environment.
Strong AI/ML and Data Science expertise, including classic ML and GenAI, with a solid software engineering foundation and hands-on experience building AI/ML solutions.
Understanding of data and ML infrastructure, including data quality, feature/data pipelines, model serving, observability, deployment, and lifecycle management.
Strong system design and architecture skills.
Proactive, ownership-driven, and results-oriented, with a strong product mindset.
Open to feedback and comfortable challenging technical decisions constructively.
Why us?
Top Tech company in Digital Health: Work in a fast-growing, innovative environment where your impact is visible.True impact in healthcare: Contribute to a unique platform with the potential to improve health for millions.International team: Join colleagues from 14+ nationalities, united by a shared vision.
Hiring Process
Recruiter ScreeningLeadership InterviewTechnical Deep DiveDecision