Utilize existing data ingestion and delivery platforms to "teach" models to understand the physical world, filling a critical expertise gap in the data center industry.
Use telemetry tools to analyze sensor data across mechanical (chillers, pumps) and electrical (UPS, switchgear, power feeds) systems to identify "failure signatures" for LLM-driven monitoring tool.
Act as a primary user of platforms, identifying gaps in current mechanisms and collaborating with Engineering to influence future features and data quality.
Translate raw telemetry into "SME-level" logic and directions used by the LLM tool to guide data center operators in real-time.
Cultivate deep domain expertise in all facets of data center infrastructure.
Move from shadowing peers to directly supporting customers, using the platform to provide clear, data-backed direction on complex problems.
Oversee pilot projects to test how AI-driven SME tool interprets real-world stressors, ensuring the output is operationally realistic, accurate, and actionable.
Remain agile and proactive in a fast-moving team environment.
Requirements
2–3 years of professional relevant experience
Bachelor’s degree in Mechanical Engineering, Electrical Engineering, Control Theory, or a related field that provides a foundation in physical systems and thermodynamics.
A deep, innate interest in using data to diagnose how and why systems fail. You are a "tinkerer" who prefers solving real-world problems over theoretical research.
Strong Python skills and experience with data manipulation libraries (Pandas/NumPy) to perform custom analysis outside of standard tooling.
Ability to explain complex diagnostic findings clearly and persuasively to both technical peers and non-domain stakeholders.
A proven ability to look at a problem without preconceived notions and figure out solutions either independently or via team collaboration.
Demonstrated commitment to Transparency, Collaboration, and Ownership—especially in environments where reliability and learning from failure are paramount.
Tech Stack
Numpy
Pandas
Python
Benefits
Fast-paced, team-oriented environment where your work directly shapes the company’s direction.
We are a 100% remote company.
Competitive compensation & meaningful equity.
Outsized responsibilities & professional development.
Training is foundational; functional, customer immersion, and development training.
Medical, dental, and vision insurance (exact benefits vary by region).
Unlimited paid time off, with a required minimum of 20 days per year.
Paid parental leave (exact benefits vary by region).
Flexible stipends to support your workspace, well-being, and continued professional development.