Staff AI/ML Engineer (all) at Xolife

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.

• 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.

• 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 .

• 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.

• Recruiter Screening
• Leadership Interview
• Technical Deep Dive
• Decision

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