Senior Staff AI Engineer, Applied AI for Patient (Remote)

SportsTechJobs; United States; Remote; USD 180,000 - 240,000; Full time

Benefits offered by this job

Remote work

Health benefits

401(k) plan

Parental leave

Wellness stipend

Home office stipend

Job summary

Rula is seeking a Sr. Staff Engineer – Applied AI, Patient to lead the design, development, and deployment of AI-powered patient experiences.

This remote-first role emphasizes building scalable ML systems, reusable infrastructure, and collaboration with the ML team on architectural decisions. You will own high-impact projects across matching, ranking, personalization, onboarding, and sequencing, guiding teams toward reliable, performant AI services while maintaining a strong emphasis on safety

Qualifications

• 10+ years of software and/or ML engineering experience with measurable product or business impact.
• Significant Python experience and production-quality coding.
• Deep hands-on ML expertise across problem formulation to deployment and monitoring.
• Experience leading across teams and guiding architectural decisions.
• Experience with recommendation/ranking/personalization/matching systems.

Responsibilities

• Develop and improve production ML models and AI-powered patient experiences.
• Lead and mentor engineers across ML lifecycle and teams.
• Shape shared ML infrastructure, standards, and tooling with the ML team.
• Evaluate and iterate on deployment, observability, and cost considerations.

Skills

Python

Production ML systems

ML infrastructure

Foundation models/GenAI

Mentoring senior engineers

Tools

Model Serving

Training Pipelines

Job description

Rula is seeking a Sr. Staff Engineer – Applied AI, Patient to lead the design, development, and deployment of AI-powered patient experiences.

This remote-first role emphasizes building scalable ML systems, reusable infrastructure, and collaboration with the ML team on architectural decisions. You will own high-impact projects across matching, ranking, personalization, onboarding, and sequencing, guiding teams toward reliable, performant AI services while maintaining a strong emphasis on safety