Staff Machine Learning Engineer (AI)

Location: Remote or hybrid; Seattle preferred, United States. Occasional travel 1–3 times per year for company-sponsored events is expected.

Pay range: $154,000–$216,000 per year; bonus eligible.

Company

hirify.global develops evidence-based content and AI-powered clinical solutions to support patient-focused healthcare, with the stability and resources of Hearst.

What you will do

• Design, build, and evolve ML engineering tooling for automated prompt tuning, content feedback loops, model benchmarking, and continuous improvement of AI-powered clinical solutions.
• Develop scalable experimentation and evaluation infrastructure for reproducible comparison and optimization of models, prompts, and AI approaches.
• Partner with Data Science, Clinical Prompt Engineering, Software Engineering, and Product teams to turn model-improvement opportunities into reliable technical solutions.
• Translate ambiguous ML and clinical AI requirements into methodologies, interfaces, and implementation plans.
• Investigate complex ML engineering problems and establish reusable engineering patterns, standards, and best practices.
• Provide technical guidance and mentorship without direct people-management responsibility.

Requirements

• Bachelor’s degree in Computer Science, Engineering, Data Science, or a related technical field, or equivalent practical experience.
• At least 6 years of relevant professional experience in machine learning engineering, software engineering, data science engineering, or a closely related technical discipline.
• Experience designing and implementing production-quality machine learning systems, tooling, or infrastructure.
• Experience with Python and modern software engineering practices.
• Ability to independently solve complex technical problems and determine effective approaches in ambiguous problem spaces.
• Experience collaborating with Data Science, Engineering, Product, or other cross-functional technical teams.

Nice to have

• Experience developing automated prompt optimization or prompt evaluation systems.
• Experience building model benchmarking frameworks or evaluation infrastructure for large language models.
• Experience developing feedback loops incorporating human or expert evaluation into ML systems.
• Experience with model observability, experimentation platforms, or MLOps.
• Experience developing reusable ML engineering frameworks or standards adopted across multiple teams.
• Strong technical communication and collaboration skills, with the ability to influence decisions through expertise rather than positional authority.
• Ability to operate effectively in ambiguous, fast-moving environments while balancing technical rigor with delivery.

Culture & Benefits

• Remote and hybrid work options with occasional company-sponsored travel.
• Medical, dental, vision, life, and disability insurance.
• 401(k), flexible spending account, and health savings account.
• 15 days of paid time off, additional front-loaded personal days, company holidays, and paid volunteer days.
• Paid parental and bonding leave, LGBTQ+ health services, and pet insurance.
• Equal employment opportunity employer committed to workplace accommodations and an inclusive workforce.