Senior AI Engineer (MLOps)

Location: San Francisco, United States; hybrid work with 3 full office days per week

Annual salary: $164,800–$247,000 USD, plus equity and benefits.

Company

hirify.global uses AI-powered, human-centered technology to scale digital healthcare for musculoskeletal conditions and deliver personalized care to more than 20 million people.

What you will do

• Design and operate production paths for AI capabilities, including deployment, serving, release automation, monitoring, rollback, orchestration, and backend integration.
• Establish service-level objectives, observability, failure-mode handling, operational ownership, and production-readiness standards for AI-backed services.
• Build safe model-promotion patterns using versioning, configuration, feature flags, canaries, rollback, and recovery mechanisms.
• Operate reliable online and batch inference systems with clear requirements for latency, availability, correctness, resilience, observability, and cost.
• Create reusable APIs, services, queues, durable workflows, monitoring, and incident-response patterns for notifications, personalization, and send-time optimization.
• Lead technical decisions, design reviews, mentoring, and cross-functional collaboration with ML Scientists, Data Scientists, Data Engineering, Product, and Software Engineering.

Requirements

• 3+ years of professional software engineering experience and 3+ years designing, building, and operating backend or distributed systems in production.
• Strong backend and distributed-systems experience, including on-call participation, incident response, debugging, and root-cause analysis.
• Production experience with ML- or AI-backed services, strong Python skills, and at least one backend language such as TypeScript, JavaScript, Go, Java, or Kotlin.
• Experience with MLOps or ML platform capabilities, online inference, batch scoring, recommendation systems, ranking, propensity models, or send-time optimization.
• Experience with AWS, Kubernetes, Docker, Kafka, PostgreSQL, Airflow, Databricks, MLflow, workflow orchestration, and long-running state systems such as Temporal or Step Functions.
• Experience integrating generative AI, LLMs, retrieval, agents, or model evaluation into production products, with awareness of privacy, security, auditability, PHI, HIPAA, or comparable constraints.

Culture & Benefits

• Hybrid working model combining remote work with three full office days per week.
• Medical, dental, and vision coverage, including support for gender-affirming care and family and fertility planning.
• Traditional or Roth 401(k) options with a 2% company match.
• Learning and development support and discounted company stock through an ESPP.
• Dog-friendly San Francisco office.