Senior Staff Engineer, Applied AI for Patient Experiences

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

Benefits offered by this job

Remote work

Transparent pay ranges

Health benefits

401(k)

Paid parental leave

EAP

Wellness stipend

Job summary

Rula, a remote-first mental health company, is seeking a Sr. Staff Engineer – Applied AI in the United States to lead and scale AI/ML-powered patient experiences.

You'll build production models, help shape infrastructure for the Patient Engineering team, and collaborate with the ML group on standards, architecture, and deployments—driving high-impact, reusable AI capabilities across products. Ideal candidates have 10+ years in software or ML, deep ML lifecycle expertise, and proven 0→1

Qualifications

• 10+ years software/ML engineering with production ML experience.
• Strong ML lifecycle leadership across problem formulation, training, evaluation, deployment, monitoring.
• Experience building shared ML infrastructure and reusable capabilities.
• Deep experience with recommender/ranking/personalization and related evaluation.
• Hands-on experience with production GenAI systems, including latency, cost, privacy/safety.

Responsibilities

• Develop and improve production ML models and AI-powered systems for Patient Engineering.
• Build reusable capabilities and infrastructure in collaboration with the ML team.
• Determine where to use custom ML, foundation models, or deterministic approaches.
• Partner with ML team to ensure scalable, reliable AI delivery.

Skills

Python

ML engineering

Production ML

Technical leadership

Experimentation

Foundation models/GenAI

Recommender systems

Tools

Model serving

Training/inference pipelines

Observability

Job description

Rula, a remote-first mental health company, is seeking a Sr. Staff Engineer – Applied AI in the United States to lead and scale AI/ML-powered patient experiences.

You'll build production models, help shape infrastructure for the Patient Engineering team, and collaborate with the ML group on standards, architecture, and deployments—driving high-impact, reusable AI capabilities across products. Ideal candidates have 10+ years in software or ML, deep ML lifecycle expertise, and proven 0→1