Senior Engineer II, Machine Learning (AI)

Location: Remote within the United States; corporate roles are not hired in AK, DE, HI, ME, MS, OK, SD, or VT. Other listed locations: San Francisco, CA; Seattle, WA; New York, NY. Office hubs are in Denver and San Francisco.

Salary: $161,500–$232,500 annually, plus equity.

Company

hirify.global develops technology, personalized nutrition, and virtual care to help reverse metabolic disease and improve clinical outcomes.

What you will do

• Translate complex clinical and operational problems into Applied AI roadmaps aligned with company OKRs.
• Design causal ML strategies and validate them through clinical experiments to measure intervention effectiveness across member segments.
• Build predictive ML models and GenAI-derived signals for product features.
• Evolve monolithic GenAI applications into reusable platform capabilities such as context retrieval, safety guardrails, treatment-guideline grounding, and chatbot orchestration.
• Own architectures spanning traditional ML and GenAI, including initiatives such as Next Best Action support and care-team triage.
• Establish evaluation frameworks, experimentation practices, code-quality standards, and safety guardrails while mentoring ML and software engineers.

Requirements

• 8+ years of experience developing and deploying production-grade machine learning systems, including technical leadership across multi-quarter initiatives.
• Experience with causal inference and causal ML frameworks, including Double ML, CATE estimation, instrumental variables, or uplift modeling, applied to observational and experimental data.
• Strong foundation in predictive modeling, tree-based models such as XGBoost, and time-series analysis of structured longitudinal data.
• Experience building GenAI architectures involving LLM integration, RAG, evaluation, and safety guardrails.
• Ability to communicate complex AI concepts as clear business strategy for senior executives, product partners, and clinical stakeholders.
• Experience establishing responsible, high-leverage practices for AI-assisted development.

Nice to have

• Clinical or health-tech ML experience, including patient-outcome prediction, risk stratification, or biomarker modeling.
• Experience designing reusable platform capabilities or shared services instead of single-use models or applications.
• Previous ML team leadership or management experience, with interest in returning to deep technical work as a senior individual contributor.

Culture & Benefits

• Remote-first work with a distributed team and office hubs in Denver and San Francisco.
• Culture emphasizes patient and employee well-being, ownership, initiative, transparency, trust, and empowerment.
• Evidence-based decision-making, positive impact, rapid iteration, and low-ego collaboration are valued.
• Work may involve sensitive patient information governed by HIPAA; security and privacy procedures and training are required.
• Compensation is location-based and depends on qualifications and experience; equity is offered.