Senior MLOps Engineer (AI)

Location: United States; remote workplace

Company

hirify.global develops AI technology for healthcare workflows, with a focus on improving patient outcomes and health equity.

What you will do

• Design and operate end-to-end ML platforms covering data ingestion, feature engineering, training, evaluation, deployment, and monitoring.
• Build CI/CD pipelines for ML and LLM systems, including testing, packaging, versioning, reproducibility, approvals, automated rollbacks, and safe releases.
• Develop scalable GCP training and deployment infrastructure using containers and orchestration, including distributed training, GPU scheduling, autoscaling, and cost controls.
• Build LLM delivery pipelines covering prompt versioning, retrieval, orchestration, evaluation, deployment, monitoring, and continuous improvement.
• Create evaluation and observability systems for model performance, drift, bias and fairness signals, latency, throughput, data quality, retrieval quality, token usage, and hallucination indicators.
• Implement security, privacy, governance, and healthcare compliance controls, including guardrails, auditability, PHI/PII handling, prompt-injection defenses, and structured output validation.

Requirements

• 6+ years of software or platform engineering experience, including 4+ years operating ML systems in production or equivalent depth.
• Strong experience with ML engineering, including training pipelines, evaluation, deployment patterns, monitoring, and iteration loops.
• Production-grade Python experience building APIs and services.
• Hands-on experience with production LLM systems.
• Strong experience with GCP services and cloud-native patterns, including Vertex AI and/or managed vector search on GCP.
• Experience with Docker, Kubernetes/GKE, and/or Cloud Run.

Culture & Benefits

• Competitive salary and benefits package.
• Flexible working arrangements, with remote or hybrid options available.
• Work on AI technology designed to impact patient outcomes and health equity.
• Continuous learning and access to current AI and healthcare tools and advancements.