Staff Ml Engineer (Applied AI)

TL;DR

Staff Ml Engineer (Applied AI): Develop and optimize production ML and LLM systems for personalized clinical care with an accent on fine-tuning large language models and preference optimization techniques. Focus on designing rigorous evaluation frameworks, driving technical strategy, and mentoring engineers in a hybrid Europe-based environment.

Location: Must be based in Portugal with a valid EU visa

Company

hirify.global is a high-tech startup shifting healthcare from human-first to AI-first through its AI Care platform, delivering digital care with clinical quality and accessibility.

What you will do

• Own complex ML problems end-to-end, including fine-tuning LLMs for clinical outcomes.
• Define technical strategy for model development, evaluation, and optimization in clinical AI.
• Build and optimize production LLM systems with fine-tuning pipelines and preference optimization.
• Work across the full AI stack from data preparation to production deployment and monitoring.
• Collaborate with Product, Clinical, and Engineering teams to ensure problem-solving alignment.
• Mentor engineers and establish best ML engineering practices.

Requirements

• Deep expertise in production ML systems with a track record of solving complex problems.
• Experience fine-tuning, evaluating, and deploying LLMs in production.
• Knowledge of preference optimization techniques like RLHF and DPO.
• Strong ML fundamentals and ability to design rigorous evaluation frameworks.
• End-to-end ownership of ambiguous and complex ML problems.
• Excellent engineering skills including distributed systems and debugging ML pipelines.
• Must be based in Portugal with a valid EU visa.

Nice to have

• Experience with healthcare AI or clinical applications.
• Track record designing evaluation frameworks for specialized LLM domains.
• Contributions to the ML community via open source or technical writing.

Culture & Benefits

• Stimulating, fast-paced environment with room for creativity.
• Competitive salary and career development opportunities.
• Flexible hours with remote or hybrid work policy and unlimited vacation.
• Health, dental, and vision insurance; meal allowance; equity shares.
• Remote work allowance and access to health and well-being programs.
• English classes and flexible working hours.

Hiring process

• 30-minute call with recruiter.
• 30-minute call with initial screener.
• Take-home assignment to be completed within one week.
• One-hour general skills and working principles interview.
• One-hour mindset and cultural fit interview.