Senior Staff Engineer - Applied AI for Patient Experience

Rula; United States; À distance; USD 180 000 - 240 000; Plein temps

Avantages offerts par ce poste

Remote work in US

401(k) plan

Health, dental, vision insurance

Parental leave

Employee assistance program

Home office equipment

Pay/benefits not geo-locked

Company shutdown weeks

Résumé du poste

Rula seeks a Sr. Staff Engineer – Applied AI, Patient to lead hands-on ML work across patient experiences, including matching, ranking, recommendations and onboarding.

You will advance production models, build reusable capabilities, and collaborate closely with the ML team on infrastructure, standards, and architecture decisions. You will drive 0→1 and 1→n advancements, evaluate model tradeoffs (custom ML vs foundation models), and mentor senior engineers while shaping a scalable, compliant AI

Qualifications

• Deep hands-on ML expertise across the ML lifecycle, from data and feature engineering to deployment and monitoring.
• Proven ability to design and scale production ML systems with measurable impact.
• Strong Python proficiency and experience with large-scale model evaluation.

Responsabilités

• Lead hands-on ML efforts for patient experiences, including matching, ranking, and personalization.
• Build reusable ML infrastructure and partner with ML team on standards and architecture decisions.
• Evaluate tradeoffs between custom ML, foundation models, and deterministic approaches.
• Mentor engineers and drive high-quality delivery of AI/ML-powered patient experiences.

Connaissances

ML leadership

Production ML

Model evaluation

Python

System design

Foundation models

Description du poste

Rula seeks a Sr. Staff Engineer – Applied AI, Patient to lead hands-on ML work across patient experiences, including matching, ranking, recommendations and onboarding.

You will advance production models, build reusable capabilities, and collaborate closely with the ML team on infrastructure, standards, and architecture decisions. You will drive 0→1 and 1→n advancements, evaluate model tradeoffs (custom ML vs foundation models), and mentor senior engineers while shaping a scalable, compliant AI