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Principal AI Engineer - Personalization and Recommendation (Remote)
RulaRemote - United States · Remote · full time · Principal
$282,000 – $370,650
Listed on Rula’s own careers site. You apply with them directly — we never stand between you and the employer.
What this role is
This role leads the design and deployment of AI and machine learning systems that power patient-provider matching and personalization across a mental healthcare platform. It suits experienced ML engineers who want to apply their expertise to high-stakes healthcare problems, shipping production systems that directly improve access to care.
Our summary, not Rula’s wording. The full posting is on their site.
Skills this role names
- A/B Testing
- Elasticsearch
- Gemini
- Go
- Java
- LLMs (Large Language Models)
- Milvus
- OpenAI
- Pinecone
- Python
- Retrieval-Augmented Generation (RAG)
- TypeScript
- Vector Databases
- Weaviate
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What they ask for
Required
- 10+ years software engineering experience
- 7+ years designing and scaling distributed systems
- 5+ years building and deploying production ML applications
- 5+ years building and optimizing search, ranking, relevance, or recommendation engines at scale
- 5+ years hands-on Python programming
- 2+ years building AI-powered products with foundation models
- 2+ years backend language experience (TypeScript, Java, or Go)
- Experience with traditional search/retrieval infrastructure (Elasticsearch, OpenSearch)
- Experience with modern vector databases (Pinecone, Weaviate, FAISS, Milvus)
- 3+ years MLOps and data pipelines experience
- 3+ years experience with rigorous evaluation systems (offline metrics, online A/B testing)
- Demonstrated ability to define technical strategy for AI/ML infrastructure
Nice to have
- Architecting secure and compliant AI solutions in regulated environments (HIPAA, GDPR)
- Familiarity with human-in-the-loop systems and clinical decision support frameworks
- Designing evaluation pipelines for human alignment, factual accuracy, or model interpretability
- Open-source contributions to AI frameworks or applied research in NLP, healthcare AI, or GenAI safety
- Experience contributing to early-stage team growth
- Leading or mentoring engineering teams in AI, ML platform, or applied research domains