Phaidra is building the future of industrial automation.

The world today is filled with static, monolithic infrastructure. Factories, power plants, buildings, etc. operate the same they've operated for decades — because the controls programming is hard-coded. Thousands of lines of rules and heuristics that define how the machines interact with each other. The result of all this hard-coding is that facilities are frozen in time, unable to adapt to their environment while their performance slowly degrades.

Phaidra creates AI-powered control systems for the industrial sector, enabling industrial facilities to automatically learn and improve over time.

Specifically:

We use reinforcement learning algorithms to provide this intelligence, converting raw sensor data into high-value actions and decisions.
We focus on industrial applications, which tend to be well-sensorized with measurable KPIs — perfect for reinforcement learning.
We enable domain experts (our users) to configure the AI control systems (i.e. agents) without writing code. They define what they want their AI agents to do, and we do it for them.

Our team has a track record of applying AI to some of the toughest problems. From achieving superhuman performance with DeepMind's AlphaGo, to reducing the energy required to cool Google's Data Centers by 40%, we deeply understand AI and how to apply it in production for massive impact.

Phaidra’s ability to achieve its mission is determined by our ability to work together — as defined by our core values: Transparency, Collaboration, Operational Excellence, Ownership, and Empathy. We seek individuals who embody these values, as they are instrumental in ensuring our team consistently delivers excellence and fosters an engaging and supportive culture

Phaidra is based in the USA, but we are 100% remote with no physical office. We hire employees internationally with the help of our partner, OysterHR. Our team is currently located throughout the USA, Canada, UK, Italy, Sweden, Spain, Portugal, the Netherlands, Singapore, Australia, and India.

We are seeking a team member located within one of the following areas: UK, USA, or Canada.

In the United States, we accept applicants located in the following states: California, Colorado, Connecticut, Georgia, Florida, Indiana, Maryland, Minnesota, Missouri, Nebraska, New York, North Carolina, Pennsylvania, South Carolina, Tennessee, Texas, Virginia, Washington.

In Canada, we accept applicants located in the following provinces: Ontario, British Columbia, and Alberta.

Responsibilities

Define and maintain a domain-accurate electrical system ontology for data centers, ensuring customer system data reflects real-world electrical infrastructure, dependencies, and failure modes rather than abstract or purely data-driven representations.
Apply deep knowledge of data center electrical systems to interpret telemetry from sensors, smart meters, and facility management systems, identifying early indicators of equipment degradation or abnormal behavior originating from customer-owned infrastructure.
Specify, constrain, and validate analytical approaches—including statistical methods and machine learning—to detect anomalies in power usage, voltage stability, load behavior, and UPS/battery systems, ensuring outputs correspond to meaningful electrical risk rather than statistical novelty.
Design and refine automated detection and alerting logic that mirrors how experienced operators reason about electrical system health, ensuring alerts correspond to actionable operational conditions such as unsafe load distributions, power anomalies, or loss of redundancy.
Perform post-incident and post-anomaly analysis by correlating electrical, mechanical, and environmental signals to determine root causes and evaluate how accurately the product represented system behavior during customer incidents.
Collaborate with customer-facing and product teams to translate anomaly insights into actionable guidance, helping customers recognize poor maintenance practices, reduce unplanned downtime, and improve overall reliability and PUE.
Design, implement, and continuously refine rules-based electrical fault detection logic grounded in real data center operating experience, ensuring failure conditions are identified before they result in customer-visible impact.
Grow internal expertise in data center electrical systems by sharing operational knowledge, failure patterns, and lessons learned from real-world infrastructure behavior.

This role is not responsible for real-time incident response or on-call operations; its value comes from applying prior operational experience to improve product performance over time. This role is not a research or experimentation position; correctness, operational realism, and alignment with real data center electrical behavior take priority over model novelty.

Key Qualifications

Minimum of 3 years of direct experience operating or monitoring electrical power systems within data center environments, including hands-on exposure to live, production infrastructure and participation in operational decision-making where uptime, redundancy, and recovery constraints materially influenced outcomes.
Bachelor’s degree in electrical engineering, power systems engineering, energy systems, or a closely related discipline or equivalent professional experience involving sustained, hands-on engagement with data center electrical infrastructure beyond purely procedural or observational roles.
Deep, working understanding of data center electrical power systems—including power quality, load balancing, redundancy architectures (e.g., A/B paths), harmonics, fault detection, and protective relaying—sufficient to interpret abnormal behavior during live operations and translate those realities into product requirements or improvements.
Proven ability to identify recurring electrical or operational patterns in data center environments and contribute to durable, scalable solutions—particularly by capturing lessons learned and applying them to system or product improvements.
Ability to communicate complex electrical system behavior and operational risk clearly to both technical peers and non-domain stakeholders, particularly in post-incident analysis, product retrospectives, or reviews of how systems performed under stress.
Demonstrated alignment with company values—Transparency, Collaboration, Operational Excellence, Ownership, and Empathy—especially in environments where reliability, trust, and learning from failure matter more than individual heroics.
Demonstrated expert use of system telemetry, historical performance data, and real-time signals to assess data center electrical system health—particularly to evaluate how systems behave during maintenance or incident conditions and where standard operating procedures fall short.

Preferred Skills & Experience

Proven experience analyzing, monitoring, and interpreting electrical distribution systems in data center environments, including substations, UPS systems, batteries, switchgear, PDUs, and stand-by generators, with a focus on understanding operational behavior and failure modes rather than day-to-day maintenance execution.
Hands-on experience working with SCADA, BMS, or energy monitoring systems, including sensor integration and data acquisition, applied in a real-world operational context to understand system behavior and detect abnormal conditions.
Experience designing and validating rules-based detection logic, thresholds, or analytics to identify electrical faults or abnormal operating conditions, grounded in practical operational experience rather than experimental modeling.
Demonstrated ability to apply machine learning or advanced analytics as a tool to enhance fault detection, predictive insights, or energy optimization, with outputs validated against real electrical system behavior.
Experience with time-series analysis, signal processing, or predictive modeling for power and thermal performance, applied to interpret real operational signals and guide actionable recommendations rather than generate research outputs.

Senior Electrical Systems Specialist (Data Center Reliability)

Americas

Remote

Senior

Phaidra