SlipstreamJobs tracks this role from the company's public career site. Apply directly on the employer's site.
Rula is hiring a Senior Staff Engineer for Applied AI to lead the development and scaling of AI/ML-powered patient experiences across matching, ranking, recommendations, onboarding, and personalization. This is a deeply hands-on technical leadership role where you'll develop and improve production models and AI-powered systems, build critical capabilities needed by the Patient Engineering team, and partner closely with Rula's ML team on shared infrastructure, models, standards, and architectural decisions.
You won't own a single model or product surface. Instead, you'll identify and tackle the highest-leverage Applied AI problems—whether that means developing models, building reusable capabilities, improving existing systems, or determining whether a problem is best solved with custom ML, a foundation model/AI service, deterministic software, or a hybrid approach.
Rula is at an important inflection point in its ML journey. The company already has ML models and pipelines powering product experiences, with additional capabilities under development. However, much of the engineering foundation required to develop, deploy, evaluate, and operate ML consistently at scale is still ahead. Your success will be measured by enabling Patient Engineering to build better intelligent experiences while creating a strong technical partnership with Rula's ML team—resulting in better models, reusable capabilities, and faster, higher-quality delivery of AI/ML-powered patient experiences.
Rula is a remote-first, Series C mental healthcare company focused on addiction treatment and broader mental health services. The company is committed to making mental health care accessible and evidence-based, with a mission to destigmatize mental health and treat the whole person.
REQUIREMENTS:
- 10+ years of software and/or ML engineering experience, including significant hands-on experience designing, building, deploying, and operating production ML systems with measurable product or business impact
- Proficiency in Python with experience building scalable systems and personally writing and reviewing production-quality code
- Deep hands-on ML expertise and technical leadership across the full ML lifecycle: problem formulation, data/feature engineering, model development and training, evaluation, experimentation, deployment, monitoring, and continuous improvement
- Demonstrated ability to set technical direction across teams, influence architecture, mentor senior engineers, and exercise strong judgment about when to use custom ML, foundation models/AI services, deterministic approaches, or hybrids
- Demonstrated 0→1 experience building shared ML infrastructure or reusable capabilities adopted across teams (e.g., feature infrastructure, training/inference pipelines, model serving, evaluation, observability, lifecycle tooling)
- Deep experience with recommendation, ranking, relevance, personalization, search, or matching systems, including rigorous evaluation connecting offline model performance to online experiments and product/business outcomes
- Hands-on experience building and operating modern foundation model/GenAI systems in production, including evaluation, reliability, latency, cost, privacy/safety, and operational tradeoffs
PREFERRED:
- Experience helping an organization evolve from early-stage or ad hoc ML development toward mature ML engineering practices
- Experience operating ML systems in healthcare, financial services, or another regulated/high-trust environment
