Senior Staff Data Engineer (ML Platform)

Location: Hybrid role based in the San Francisco office, with in-person attendance required three days per week. Remote days follow core business hours; occasional off-site or on-site events may occur.

Salary: $240,000–$360,000 annual salary, plus equity and benefits.

Company

hirify.global uses AI-powered, human-centered technology to scale healthcare delivery for musculoskeletal conditions and improve care outcomes, experiences, and costs.

What you will do

• Set the long-term technical vision and architectural direction for streaming, batch, data modeling, and serving layers.
• Design infrastructure connecting data platform capabilities with ML workloads, including feature pipelines, feature stores, and serving layers.
• Establish standards for data modeling, schema governance, testing, pipeline reliability, and code quality.
• Lead cross-organizational initiatives involving data contracts, schema evolution, and coordination between data producers and consumers.
• Improve platform-level observability, data quality, incident response, reliability, and cost efficiency.
• Mentor senior engineers and communicate architectural tradeoffs to engineering, Data Science, product teams, and leadership.

Requirements

• 10+ years of hands-on data engineering experience, including significant platform or infrastructure work.
• Experience architecting batch and streaming data systems using technologies such as Kafka, Flink, Spark, or equivalent.
• Strong Python and SQL skills with deep experience in distributed data processing and data platform design.
• Experience building ML platform infrastructure such as feature pipelines, feature stores, model serving, or MLOps tooling.
• Track record of setting technical direction across multiple teams without formal authority and mentoring senior engineers.
• Bachelor’s degree or equivalent in Computer Science, Engineering, or a related technical field.

Nice to have

• Experience in a growth-stage or scaling company where foundational architecture decisions were required.
• Experience with data contracts, schema design, governance, and data quality improvements.
• Experience in HIPAA, SOC 2, or similarly regulated environments.
• Familiarity with Delta Lake, MLflow, and Unity Catalog in the Databricks ecosystem.
• Experience using AI-assisted development tools.

Culture & Benefits

• Hybrid work arrangement with flexibility on remote days.
• Medical, dental, and vision coverage for employees and family members.
• Gender-affirming care, family and fertility planning support, and healthcare travel reimbursements.
• Traditional or Roth 401(k) options with a 2% company match.
• Learning and development stipend, discounted company stock through an ESPP, and a dog-friendly office.