Staff AI/ML Engineer (AI)

Location: Remote within the United States, with optional in-person collaboration at the San Francisco office

Company

hirify.global develops AI-driven, data-powered, privacy-compliant healthcare engagement solutions, including MyHealthTeam patient communities and prescription fulfillment technology.

What you will do

• Build end-to-end ML and LLM features from problem definition through deployment, evaluation, and monitoring.
• Develop retrieval-augmented generation, tool-use, orchestration, and structured extraction workflows for consumer health experiences.
• Convert posts, comments, messages, and search queries into structured signals such as topics, entities, intent, sentiment, and safety flags.
• Create training, inference, evaluation, and analytics pipelines using batch or streaming processing.
• Design quality and safety evaluation systems, including offline metrics, golden datasets, human review, A/B testing alignment, red-teaming, and incident response.
• Lead applied AI architecture and technical direction, establish reusable platforms and best practices, and mentor engineers while collaborating with Product, Engineering, Data, and clinical experts.

Requirements

• 8+ years of experience building and shipping production ML systems, or equivalent demonstrable impact.
• Strong Python skills and experience with ML/LLM libraries and tooling such as Hugging Face, LangChain, or LangGraph.
• Experience designing production-grade training, inference, and evaluation pipelines and operating models with monitoring, rollbacks, and incident handling.
• Strong foundations in NLP, deep learning, statistical reasoning, and ML evaluation.
• Experience with MLOps, including versioning, reproducibility, CI/CD, model registries, feature and data management, and infrastructure collaboration.
• Experience processing large-scale data with Databricks, Spark, or equivalent distributed technologies, plus the ability to translate ambiguous product needs into measurable ML outcomes.

Nice to have

• Experience with RAG, vector databases, hybrid search, ranking, recommendations, and query understanding.
• Healthcare or regulated-environment experience, including privacy by design, auditability, safety reviews, or HIPAA/PHI familiarity.
• Experience with streaming data, experimentation platforms, causal or measurement analysis, and LLM safety systems.
• Ability to prototype end-to-end experiences with tools such as Streamlit or Gradio.

Culture & Benefits

• Remote-first engineering environment with optional in-person collaboration in San Francisco.
• Mission-driven work supporting millions of people living with chronic and rare conditions.
• High-ownership culture with small teams, fast shipping, and visible product impact.
• Close collaboration across product, data, engineering, and healthcare domain expertise.
• Opportunities for professional growth in applied AI and continuous learning.

Hiring process

• Submit a resume and answer why MyHealthTeam’s mission matters to you.
• Provide an example of a production ML or LLM system shipped and explain how it was evaluated.