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AI Lab Equipment Maintenance Scheduling Engineer

James Yamamoto

Full-time · Job · Los_Angeles

About the role

You'll join a lab operations squad of six, working alongside scientists who lose real research time every time a critical piece of lab equipment fails without warning between scheduled maintenance windows. You will build a predictive maintenance scheduling model using equipment usage logs, sensor telemetry, and historical failure records, recommending maintenance windows that minimize both downtime and unnecessary servicing. You'll work closely with lab operations managers across three research sites to make sure recommendations actually fit around active experiment schedules, not just equipment convenience.

Responsibilities

  • Build a predictive maintenance scheduling model using equipment usage and sensor data
  • Own the Snowflake-based data pipeline aggregating telemetry across three research sites
  • Partner with lab operations managers to align maintenance windows with experiment schedules
  • Validate scheduling recommendations against actual downtime and servicing outcomes
  • Maintain ETL jobs feeding equipment telemetry into the scheduling model

Requirements

  • 3+ years in applied data science or predictive maintenance modeling
  • Strong Python and SQL skills
  • Experience with Snowflake or comparable cloud data warehouses
  • Comfortable coordinating across multiple physical research sites

Benefits

  • Fully remote position
  • Health, dental, and vision insurance
  • Equity package
  • Annual research site visit opportunities

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Job Type

Full-time

Level

Mid-Level

Language

English

Salary Range

$100k – $130k / year

AI Expertise

data science & analytics Automation & AI Workflows

Skills

python sql etl snowflake

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