Staff AI/ML Engineer
Xolife
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About the Company
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 Screening Leadership Interview Technical Deep Dive Decision
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