Remote Principal AI Engineer: Personalization

Openkrill; United States; Remote; USD 150,000 - 190,000; Full time

Benefits offered by this job

Remote work

Health benefits

401(k) plan

Paid parental leave

Wellness stipend

Home office stipend

Employee Assistance Program (EAP)

Time-off weeks

In-person team events

Open-source contributions encouraged

Job summary

Rula is a remote-first company hiring in most US states (excluding Hawaii). This role leads applied AI/ML solutions powering patient-provider matching, clinical workflows, and patient engagement. You will focus on search ranking, relevance, and personalization while building scalable ML foundations.

You’ll develop and fine‑tune models (Learning-to-Rank, embeddings, LLMs), design AI architectures, and lead ML infrastructure to ship features that improve care and user trust.

Qualifications

• 10+ years in software engineering including 7+ years designing and scaling distributed systems.
• 5+ years building and deploying production-grade ML applications.
• 5+ years building and optimizing search/relevance/recommendation engines at scale.
• 5+ years Python + at least one backend language; 2+ years using foundation models & LLM integration.
• 3+ years with Elasticsearch/OpenSearch and modern vector databases.

Responsibilities

• Own applied AI/ML solutions powering patient-provider matching and clinical workflows.
• Develop production-grade AI systems and scalable ML infrastructure.
• Design product-facing AI architectures and guide ML platform decisions.
• Ship features that improve match quality and user experience while ensuring safety.

Skills

Distributed systems

Search & ranking

Python

Backend languages

AI/ML integration

Elasticsearch/OpenSearch

Vector databases

MLOps

Data pipelines

Tools

Elasticsearch

OpenSearch

Pinecone

Weaviate

FAISS

Milvus

Job description

Rula is a remote-first company hiring in most US states (excluding Hawaii). This role leads applied AI/ML solutions powering patient-provider matching, clinical workflows, and patient engagement. You will focus on search ranking, relevance, and personalization while building scalable ML foundations.

You’ll develop and fine‑tune models (Learning-to-Rank, embeddings, LLMs), design AI architectures, and lead ML infrastructure to ship features that improve care and user trust.