Staff Machine Learning Operations Engineer (AI)

Location: New York City office, Financial District; required in-office work on Tuesday, Wednesday, and Thursday

Salary: $298,000–$351,000 per year, plus equity incentives and benefits

Company

hirify.global uses proprietary clinical metrics and large-scale healthcare data to identify high-performing doctors and help employers and members access higher-quality, lower-cost care.

What you will do

• Own the reliability, performance, functionality, cost-efficiency, SLOs, observability, and on-call operations of production machine learning systems.
• Architect the ML platform, including feature stores, model registries, data infrastructure, and standardized service patterns.
• Build automated, PR-driven ML CI/CD workflows with data quality checks and statistical model validation before deployment.
• Reduce infrastructure costs and latency through architecture improvements, hardware selection, and model optimization.
• Establish MLOps workflows, standards, KPIs, and onboarding foundations for a future team.
• Design automated data drift and concept drift monitoring to detect model degradation and support future continuous training.

Requirements

• 7+ years of software engineering experience, including significant experience operating ML or data-intensive systems in production at scale.
• Deep experience with model serving, feature stores, model registries, and ML CI/CD.
• Strong platform engineering fundamentals across Kubernetes, containerization, AWS, Terraform/IaC, observability, and incident response.
• Experience designing ML platforms or substantial platform components, with sound build-versus-buy judgment.
• Ability to set technical direction and collaborate with ML, data, platform, data science, and product engineering teams.
• Must work from the New York City office three days per week; employment visa sponsorship is not available.

Nice to have

• Healthcare, regulated-data, or other high-stakes production ML experience.

Culture & Benefits

• Mission-driven work focused on improving healthcare outcomes and reducing costs.
• High ownership, autonomy, urgency, accountability, and direct feedback.
• Coaching and opportunities to take on ambitious technical problems.
• Flexible PTO, medical, dental, and vision plan options, 401(k), Teladoc Health, and equity incentives.