Principal AI Engineer - Personalization and Recommendation (Remote)
Rula · Remote - United States
About this role
## Principal AI Engineer — Personalization and Recommendation (Remote) ### About the Role At Rula, this role owns the applied AI and ML solutions that determine **what, how, and how well AI shows up across mental healthcare**. The focus is on building **production-grade** systems that power: - **Patient-provider matching** - **Clinical workflows** - **Patient engagement** While your near-term focus will be **search ranking, relevance, and patient-provider matching**, your broader scope includes **personalization and recommendation strategies** and the **foundational ML platforms** that support them at scale. You’ll work at the intersection of **applied research, system architecture, and real-world clinical constraints**, including: - Building **recommendation engines** and **retrieval models** - Applying **NLP** and **generative AI** to clinical workflows - Setting **technical standards for AI safety** - Making principal decisions about introducing ML into a **high-stakes** environment This is a deeply hands-on role with real technical ownership—developing and fine-tuning models (e.g., **Learning-to-Rank, embeddings, recommendation algorithms, and LLMs**), designing AI architectures and ML infrastructure, and unblocking complex engineering problems. ### What You’ll Do - Develop and fine-tune applied ML models for personalization and recommendation - Design product-facing AI architectures and core ML infrastructure - Improve match quality and user experience through shipped AI features - Build scalable, durable AI foundations others can confidently build on - Set direction for relevance/recommendation systems and the broader AI ecosystem ### Required Qualifications - **10+ years** software engineering, including: - **7+ years** designing and scaling distributed systems - **5+ years** building and deploying production-grade ML applications - **5+ years** hands-on experience building/optimizing search, ranking, relevance, or recommendation engines at scale (e.g., **Learning-to-Rank, collaborative filtering, deep recommender systems, semantic vector search**) - **5+ years** strong programming experience in **Python** and at least one backend language (**TypeScript, Java, or Go** preferred), plus **2+ years** building AI-powered products using foundation models (e.g., **OpenAI, Anthropic, Gemini**) and LLM integration patterns (**RAG, agents**, etc.) - Proven experience with both: - Traditional search/retrieval infrastructure (e.g., **Elasticsearch, OpenSearch**) - Vector databases (e.g., **Pinecone, Weaviate, FAISS, Milvus**) - **3+ years** MLOps, data pipelines, and rigorous evaluation systems (offline metrics like **NDCG/MAP**, online **A/B testing**), with ability to define technical strategy and guide AI/ML infrastructure ### Preferred Qualifications Not required to apply—apply even if you don’t meet every preferred item. - Experience architecting **secure and compliant** AI in regulated environments (**HIPAA, GDPR**, etc.) - Familiarity with **human-in-the-loop** systems and clinical decision support frameworks - Experience designing evaluation pipelines for **human alignment, factual accuracy, or interpretability** - Contributions to open-source AI frameworks or applied research in **NLP, healthcare AI, or GenAI safety** - Experience contributing to early-stage team growth (**0 → 1**) - Experience leading or mentoring engineering teams in **AI/ML platforms** or **applied research** ### Remote & Location - **Remote-firs
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